Leveraging Blogging Activity on Tumblr to Infer Demographics and Interests of Users for Advertising Purposes Mihajlo Grbovic, Vladan Radosavljevic, Nemanja Djuric Narayan Bhamidipati, Ananth Nagarajan Yahoo Labs {mihajlo, vladan, nemanja}@yahoo-inc.com 701 First Ave, Sunnyvale, CA, USA ABSTRACT 1. INTRODUCTION As one of the leading platforms for creative content, Tumblr In recent years, online social networks have evolved to be- offers advertisers a unique way of creating brand identity. come an important part of life for online users of all demo- Advertisers can tell their story through images, animation, graphic and socio-economic backgrounds. They allow users text, music, video and more, and they can promote that to easily stay in touch with their friends and family, discuss content by sponsoring it to appear as an advertisement in everyday events, or share their interests with other users the streams of Tumblr users. In this paper, we present a with the click of a button. Tumblr is one such social net- framework that enabled one of the key targeted advertis- work, representing one of the most popular and fastest grow- ing components for Tumblr, specifically, gender and interest ing networks on the web. Hundreds of millions of people targeting. We describe the main challenges involved in the around the world come every month to Tumblr to find, fol- development of the framework, which include the creation low, and share what they love. The Tumblr network is a gold of a ground truth for training gender prediction models, as mine of content, comprising of 200 million blogs on different well as mapping Tumblr content to an interest taxonomy. topics such as travel, sports, and music, where 85 million For purposes of inferring user interests, we propose a novel user posts are published on a daily basis. This wealth of semi-supervised neural language model for categorization of user-generated data opens a great opportunity for advertis- Tumblr content (i.e., post tags and post keywords). The ers, allowing them to promote their products through high- model was trained on a large-scale data set consisting of 6.8 quality targeting campaigns to both blog visitors and blog billion user posts, with a very limited amount of categorized owners [16]. keywords, and was shown to have superior performance over The standard, prevalent form of advertising on Tumblr is the baseline models. We successfully deployed gender and through sponsored posts that appear alongside regular posts interest targeting capability in Yahoo production systems, in the user’s dashboard, the central page for a Tumblr user, delivering inference for users that covers more than 90% of displaying the newest posts of followed blogs in the form the daily activities on Tumblr. Online performance results of a stream. This form of advertising, in which advertise- indicate advantages of the proposed approach, where we ob- ments resemble native content in the stream, is often referred served a 20% increase in user engagement with sponsored to as native advertising. Native advertisements are usually posts in comparison to untargeted campaigns. aesthetically beautiful and highly engaging, which typically makes them more enjoyable than regular display ads [4]. Tumblr launched its native advertising product in May of Categories and Subject Descriptors 2012. Since then, the number of advertisers (or brands) on H.2.8 [Database applications]: Data Mining the platform has grown steadily and reached a milestone of 100 advertisers in April of 2013. Moreover, most of the biggest global brands have used Tumblr to advertise and Keywords sponsored posts have generated billions of paid ad impres- sions since the launch of the Tumblr advertising product1 . data mining; computational advertising; audience modeling; In this paper, we further enhance ad targeting that Tumblr algorithms offers, allowing advertisers to specify new demographic or interest categories. This improved targeting provides adver- Permission to make digital or hard copies of all or part of this work for personal or tisers with the control and flexibility to find the audience classroom use is granted without fee provided that copies are not made or distributed they most want to reach. for profit or commercial advantage and that copies bear this notice and the full cita- Copyright c 2016 held by author(s)/owner(s); copying permitted Building of interest targeting products on social and mi- tion on the first page. Copyrights for components of this work owned by others than only for private and academic purposes. ACM must beas honored. Abstracting with credit is permitted. To copyproceedings, otherwise, or re- croblogging platforms is an important research topic, dis- Published part of the #Microposts2016 Workshop publish, to post available on servers online as CEURor to redistribute Vol-1691 to(http://ceur-ws.org/Vol-1691) lists, requires prior specific permission cussed previously by several researchers [11]. However, due and/or a fee. Request permissions from Permissions@acm.org. to its distinct characteristics, Tumblr poses novel challenges, KDD’15, August 10-13,Apr #Microposts2016, 2015,11th, Sydney, NSW,Montréal, 2016, Australia. Canada. c 2015 ACM. ISBN 978-1-4503-3664-2/15/08 ...$15.00. 1 DOI: http://dx.doi.org/10.1145/2766XXX.XXXXXXX. www.comscore.com, accessed June 2015 · #Microposts2016 · 6th Workshop on Making Sense of Microposts · @WWW2016 Figure 1: Examples of blog title (first line, bigger font) and blog description (bottom line, smaller font) which we explain in detail in this paper. In particular, the and follow, like and reblog actions. This data is publicly content and language used on Tumblr have distinct charac- available through Tumblr Firehose data source3 . Other user teristics that needed to be accounted for during the mod- activities, such as user searches on Tumblr, which blogs they eling. Users often use tags to summarize the text in their visited and where they clicked, are considered to be sensitive posts. However, the language styles used in the tags and data and were not used in any way for the development of post text are different (e.g., the tag “hp” and the word the ad targeting models. “hp” have different meanings when they appear in the posts, “Harry Potter” and “HP company”, respectively). More- 2. RELATED WORK over, unlike the popular social platform Facebook, which Personalization is defined as “the ability to proactively tai- contains a large amount of social interactions but a limited lor products and product purchasing experiences to tastes of amount of content, or the microblogging platform Twitter, individual consumers based upon their personal and prefer- which contains an intermediate amount of social interac- ence information” [7], and it has become an important topic tion and content, Tumblr represents a unique combination in recent years. Personalization of online content for individ- of a rich and diverse content platform and a dynamic so- ual users may lead to improved user experience and directly cial network. To make use of this vast advertising potential, translate into financial gains for online businesses [14]. In we propose to classify user-generated Tumblr content into a addition, personalization fosters a stronger bond between standard multi-level general-interest taxonomy 2 that adver- customers and companies, and can help in increasing user tisers commonly use for defining their targeting campaigns, loyalty and retention [2]. For these reasons it has been rec- opening doors to high-quality audience segmentation and ognized as a strategic goal and is the focus of significant modeling for purposes of ad targeting. However, inferring research efforts of major internet companies [8, 12]. categories of user posts is a challenging task, given the huge We consider personalization through the domain of ad tar- quantities of unlabeled data being posted every day and the geting [9], where the task is to find the best matching ads very limited amount of labeled data, typically obtained by to be displayed for each individual user. This improves the human editorial efforts. To this end, we propose a novel user’s online experience (as only relevant and interesting ads semi-supervised neural language model, capable of jointly are shown) and can lead to increased revenue for the adver- learning embeddings of post keywords, post tags and cate- tisers (as users are more likely to click on the ad and make a gory representations in the same feature space. The neural purchase). Due to its large impact and many open research model was trained on a large-scale data set comprising of questions, targeted advertising has garnered significant in- 6.8 billion posts, with only a fraction of categorized content. terest from the machine learning community, as witnessed Targeting pipelines described in this paper are being used by a large number of recent workshops4 . and publications to show ads to millions of users daily, and have substantially [5, 11]. improved Tumblr’s business metrics following the launch. One of the basic approaches in ad targeting is to target On our path to developing targeting capabilities for Tum- users with ads based on their demographics, such as age or blr, we first created user profiles, based on users’ Tumblr gender. Historically, this approach has proven to work better activities that include publishing blog posts, following other than targeting random users. However, while for some prod- blogs, liking posts, and other. Lastly, we aimed at build- ucts this type of targeting may be sufficient (e.g., women’s ing and delivering both demographic and interest predictive makeup, women’s clothing, man’s razors, man’s clothing), models based on the created profiles. for others it is not effective enough and a more involved We note that the privacy of our users is of critical impor- profiling of users is required. A popular method in today’s tance. Therefore, we were constrained in regards to what ad targeting that addresses this issue is known as interest data we can use. Specifically, user profiles were created targeting, in which users are assigned interest categories, solely from data which users share publicly with others, in- such as “sports” or “travel”, based on their historical be- cluding contents of blog posts, blog titles and descriptions, havior [1]. Typically, a taxonomy is used to decide on the 3 2 http://www.iab.net/QAGInitiative/overview/ gnip.com/sources/tumblr 4 taxonomy www.targetad-workshop.net 3 · #Microposts2016 · 6th Workshop on Making Sense of Microposts · @WWW2016 title body tags like reblog Figure 3: Example of Tumblr blog post Figure 2: Distribution of Tumblr post types created by a registered user is considered his or her primary blog. In addition, a very small portion of users maintain targeting categories, and a model is learned to categorize one or more secondary blogs. A Tumblr user is uniquely de- user activities and estimate their interest in each category. scribed by the blog ID of the primary blog, and throughout Interest targeting is known to build good brand awareness the paper we will use “blog” and “user” interchangeably. with relevant audience, which has already shown interest in Common user activities of Tumblr users include the fol- the corresponding category. In this paper we follow this in- lowing: 1) creating a post on one’s blog; 2) sharing a post terest targeting approach. Alternatively, advertisers may be created by another blog, called reblogging (a reblogged post interested going a step forward and optimizing for intent, will appear on the user’s blog); 3) liking a post by another typically done by assigning categories to actual ads, and blog; and 4) following another blog. Similar to Twitter, the training a machine learning model to estimate the probabil- follow connections at Tumblr are uni-directional. However, ity of an ad click in that category [17]. For each ad category unlike Twitter, users can create longer and richer content in a separate predictive model is trained, and evaluated on the the form of several post types, such as text, photo, quote, entire user population, with N users with the highest score link, chat, audio and video. The most popular types of blog selected for ad exposure. posts are photo posts and text posts, and, based on the To the best of our knowledge, the Tumblr social network analysis published in [18], together they cover more than has been considered by only a few scientific studies. In [3, 92% of all posts on Tumblr (see Figure 2). Any post type 15], the authors discuss the problem of blog recommenda- can be annotated with words starting with # that concisely tion, while in [6] they explore Tumblr social norms. How- describe the post and allow for easier browsing and search- ever, our work is the first paper that addresses ad targeting ing (called tags). Additional metadata that describes a post on Tumblr. includes photo captions in photo posts, post titles in text posts, and artists names in audio posts. An example post is shown in Figure 3. Tags, such as #gadgets or #tech, are 3. WHAT IS TUMBLR? displayed bellow the photo caption, while the buttons for re- Tumblr5 is one of the most popular social blogging plat- blog and like actions are located in the bottom right corner. forms, where users can create and share posts with the fol- Lastly, each user has a dashboard (i.e., a feed of blog posts lowers of their blogs. According to data from January 20156 , published by followed users, which is ordered in time), with there is a total of 221.6 million blogs on Tumblr, which more recent posts appearing at the top. jointly produced over 102.7 billion blog posts. With a large number of users signing up every day, Tumblr is currently 3.2 Advertising at Tumblr the fastest growing social platform7 . Advertising on Tumblr is implemented through the mech- 3.1 User activities on Tumblr anism of sponsored (or promoted) posts shown in a user’s dashboard. This is similar to how advertising works on Twit- To register for a Tumblr account, a valid e-mail address is ter and Facebook. A sponsored post can be a video, an im- required, along with a primary username (which will become age, or simply a textual post containing an advertising mes- a part of the blog URL) and a confirmation of age. A Tumblr sage. In Figure 4, we show an example of a sponsored post blog resembles a webpage, with a profile picture, blog title and how it appears on web and mobile dashboards. Sim- and blog description appearing at the top (see Figure 1), ilarly to organic (or non-promoted) posts, sponsored posts followed by a stream of blog posts bellow. The first blog can propagate from user to user in the network by means of 5 www.tumblr.com reblogs, and users can also “like” the promoted post. Both 6 www.tumblr.com/about likes and reblogs can be seen as an explicit form of accep- 7 http://t.co/3txHFRJreJ tance or endorsement of the advertising message. Moreover, 4 · #Microposts2016 · 6th Workshop on Making Sense of Microposts · @WWW2016 S THAT ARE EFFECTIVE Table 1: User data extracted from Tumblr Firehose Declared Content Actions blog title post tags reblog blog description photo captions like l images text post title follow text post body audio post artists d by the user’s first name, age, and even declared interests (e.g., statements such as “fashion addict” or “I love football”). video 4.2 Data Processing In order to improve the representation of user profiles, we crease the propose to extract keywords from available blog informa- tion. This requires a certain amount of data preparation and processing. Given the extracted blog data, including the title, content and tags, we first removed all the html tags, followed by the removal of stopwords and the forma- tion of bigrams. It is common for certain words to appear Figure 4: Example of Tumblr sponsored post together more often than some others (e.g., words “credit” and “card”), and we aim to capture those bigrams and use them in keyword-based user profiles. To detect bigrams, we just like any other posts, sponsored posts are supplemented use a procedure that counts the unigram and bigram ap- with notes on who liked and reblogged the post. pearances, and for each combination of words wi and wj it Interestingly, while user-generated, organic posts are re- calculates the following score: blogged on average 14 times, sponsored posts are reblogged count(wi , wj ) on average 10,000 times8 . We have observed that 40% of score(wi , wj ) = . (4.1) count(wi )count(wj ) engagements with sponsored posts are reblogs, likes, or fol- lows. What is more, every fourth reblog of a sponsored Finally, bigrams with a score above a certain threshold were post results in 6 downstream reblogs from followers, leading extracted from the text in blog contents. Tags, on the other to content longevity, and one third of reblogs of sponsored hand, naturally form n-grams, and we extracted them in posts are present for 30 days or more after the initial post. their original form. 4.3 User profiles 4. TUMBLR DATA Available data sources were used to create user profiles. In In this section, we describe the data sources (user ac- particular, we extracted three distinct groups of user-related tivities and post contents) utilized to create user profiles. data: 1) declared; 2) content of posts; and 3) actions. The In particular, user activities included actions such as posts, specific components included in each of the data groups are likes, follows and reblogs, while post contents included tags, listed in Table 1. From each group we extracted features to the title and body for text posts, artist names from audio represent the users as described below. posts, as well as tags and captions for photo posts. Declared data consists of information which a user pro- vided during sign-up, including keywords from the blog title 4.1 Data sources and blog description, where keywords were extracted using Once signed in onto Tumblr, a user can follow other users’ the method in Section 4.2. To create user profiles we kept blogs. The follow action is one-directional as it does not re- the most frequent keywords from blog titles and descrip- quire the follow back. For the purpose of this study, we tions, after removing stopwords such as “a”, “the”, “where”, collected a sub-graph which contained 96.9 million unique “in”. We counted the keyword frequency in a user’s blog title nodes (i.e., users), 5.1 billion edges (i.e., follows), out of and description, and stored the count along with the time which 36.4 million are bi-directional (18.2 million pairs of stamp of the latest log-in as a part of the user profile. users that follow each other). The data set included more Content features were formed from the textual contents than 26.1 billion activities on Tumblr. As discussed ear- of posts which a user either created or reblogged. The main lier, an activity log is available through a data feed called content feature types included: 1) post tags; 2) keywords Firehose. from the post title and body; 3) keywords from photo post To create user profiles for targeting, textual contents of all captions; and 4) artist names from audio posts. Tags in posts were collected, including photo captions, tags, titles posts were not tokenized, instead they were used in the form and bodies. In addition, every time a user performs a post they appear, e.g., tag “food for a vegan” was one keyword. or reblog activity, Firehose lists the user’s blog title and On the other hand, in order to extract keywords from text blog description, which we also used to represent a user. appearing in text post content, we again used the method As we can see in Figure 1, a blog title and description often from Section 4.2. We kept only the most frequently occur- provide useful information with respect to targeting, such as ring keywords, excluding stopwords. In addition, we used the most popular artist names as keywords. In this way, 8 http://yhoo.it/1vFfIAc we collected several millions of distinct keywords that were 5 · #Microposts2016 · 6th Workshop on Making Sense of Microposts · @WWW2016 tags  within  a  single  post   tags  within  a  single  post   tj-­‐n   …   tj-­‐1   tj+1   …   tj+n   tj-­‐n   …   tj-­‐1   tj+1   …   tj+n   Projec(on   Projec/on   tj   tj   c1   …   ck   j-­‐th  tag   j-­‐th  tag   j-­‐th  tag  categories   Figure 5: Unsupervised skip-gram model Figure 6: Semi-supervised skip-gram model ing platform for native advertising9 . The GIT is carefully used to obtain rich representation of user profiles. To il- derived based on Interactive Advertising Bureau (IAB) tax- lustrate content keyword extraction from our dataset, con- onomy recommendations, in order to meet advertiser needs sider that user ui at time stamp t used tag #hp five times and protect Yahoo’s interests. The GIT has a two-level hi- and tag #nba eight times, keyword football two times in erarchical structure, such that advertisers can adjust the post titles and posted an audio post with a song from artist audience reach by utilizing broader or narrower interest cat- Shakira ten times, then the resulting user profile would be: egories. The top level of the taxonomy contains 23 nodes ui = {tag : {#hp, t : 5, #nba, t : 8}, title : {f ootball, t : (e.g., “Automotive”, “Business”, “Pets”, “Travel”), while the 2}, artist : {shakira, t : 10}}. second level contains 130 nodes which represent more precise Action features include follows, likes, and reblogs. If interests (e.g., “Automotive/SUV”, “Automotive/Luxury”, user ui follows user uj at time stamp t, we create an indi- “Pets/Dogs”). cator feature f ollows : {j, t : 1} and add it to the ui ’s user profile. Similarly, if user ui likes or reblogs user uj ’s post, we create a feature that keeps record of the number of likes 5.2 Proposed semi-supervised classification m and reblogs n, as likes : {j, t : m}, reblogs : {j, t : n}, In this section, we present a novel classification approach respectively, and update the user profile accordingly. based on the recently proposed skip-gram model [13], which The described approach resulted in user profiles for a total is used to categorize keywords into the GIT taxonomy. For of 81.8 million users. The total number of unique features conciseness, we describe the proposed model on the assump- was 1.4 million, and an average user had 379.9 non-zero fea- tion that it is applied to tag categorization. However, we tures. Most of the features described above are represented used the same methodology for categorization of keywords as either binary indicators or counts of occurrences. originating from blog titles, descriptions and text, audio and image posts. We consider the task of tag classification, where the goal 5. INTEREST PREDICTION is to classify tags into a pre-defined taxonomy of interest categories. In order to address this problem, we propose The goal of our work is to infer user demographics (de- to learn tag representation in a low-dimensional space using scribed in the following section) and identify user groups neural language models that are applied to historical Tum- with interests in certain topics, such as music, travel, cook- blr posts. Let us assume that we are given N posts. In the ing or books, in order to allow advertisers to target seg- post logs found in Firehose, every post pi is recorded along mented Tumblr audiences. As the topics may be defined at with the tags tij , j = 1...M . We collected data in the form various levels of granularity, to avoid sparsity problems while pi = {tij , j = 1...Mi }, where Mi represents the number of still providing useful and actionable interest categories, user tags in the i-th post. Given the data set D = ∪N i=1 pi , the interests are often classified into a pre-determined hierarchi- objective is to find a representation of tags in which seman- cal interest taxonomy that the advertisers commonly use. tically similar tags are nearby in the representation space. However, to be able to create effective user interest classi- For this purpose, we extend ideas originating from recently fiers, one requires a sufficient amount of labeled data. Yet, proposed language models, as described in the remainder of for the problem of the scale of Tumblr interest prediction, this section. this can be a daunting task for human editors. For that The skip-gram (SG) model involves learning represen- reason we propose a novel semi-supervised classification ap- tations of tags in a low-dimensional space from post logs in proach, based on the recently proposed word2vec model [13], an unsupervised fashion, by using the notion of a blog post which efficiently and seamlessly makes use of large amounts as a “sentence” and the tags within the post as “words”, of unlabeled and a limited amount of editorially labeled data borrowing the terminology from the Natural Language Pro- for learning effective content classifiers. cessing (NLP) domain (see Figure 5). Tag representations using the skip-gram model [13] are learned by maximizing 5.1 User interest taxonomy the objective function over the entire D set of blog posts, We decided to classify keywords into the General Inter- 9 est Taxonomy (GIT), used by the Yahoo Gemini advertis- gemini.yahoo.com 6 · #Microposts2016 · 6th Workshop on Making Sense of Microposts · @WWW2016 Table 2: Examples of categorized tags anastasiabeverlyhills green_dress makeuplover dahliawolf maccosmetics fashionable motivescosmetics face_makeup makeup_brushes blackdress wedding_dress red_lipstick makeup_blogsmokeyeye smokey_eyes black_lipstick Tag Category embellished little_black_dress black_heels long_prom_dresses maquiagem eye_shadow bblogger lip_balm bridal_gown heels prom_dress summer_dress haircare bustier chic cocktail_dress mesh smokey_eye eye_brows younique beauty_guru natural_makeup beautiful_eye_shadow bath_body_products music Arts and Entertainment/Music cateye white_dress make_up bronzer lip_care beautyblog makeupforever maybelline lip_treatments eye_beauty makeup_ideas instabeauty eye_liner foundation backless_dress sugarpill nars cosmetics smokey jumpsuit bride strapless ruffle beautyguru makeupartist baby_lips lime_crime cut_out rhinestones lace_dress stilettos pout fashion Style and Fashion marykay smoky sheer eye_makeup lashes nails pretty_eye_shadow palettes motives white_lace nail_polish sundress ruffles tulle lace lips beautyblogger lip eau_de_perfume beading bridal beauty fotd beaded lipgloss mascara prom song Arts and Entertainment/Music benefit casual cat_eyes eye guru sleek smashbox flower_print eyes sparkle makeup_artist dark_lips red_lips swatches corset hairstyle sequin_dress long_skirt skincare open_back lip_makeup polka_dot minidress cutoutblue_dress eyeshadow highlight tarte party_dress art Arts and Entertainment red_lip makeupaddict kat_von_d clothes mua rimmel redlips peplum modcloth powder evening_dress makeup_tips meggy_grace naked3 blush elegance blouse maxi ilovemakeup motd weddingdress fashion_dress lips_makeup disney Arts and Entertainment/Movies make up bourjois instamakeup beautiful_dress backless sequin nail_varnish cateyes revlon cosmetology palette mask sparkly makeup_brands yellow_dress brows lip_treatment eotd formal haul purple_dress ball_gown bridesmaid_dresses liner bag pink_dress long_dress gown style Style and Fashion cocktail_dresses avon drugstore skin_care lipstick eyeliner vegas nay pinklips bigeyes greeneyes glitter nail_care contacts lorac macredlipstick makeover partydress straps dresses flowy loreal lash babylips fahion pearls bbloggers facepaint mac_cosmetics evening_gown eye_lashes elegant red_dress photography Hobbies/Photography frilly lipbalm contour lipsticks sephora couture brown_eyes sexy_eye_shadow clutch fashion_and_dressing_right lancome beautytips pink_lips chiffon skirt pink_lipstick hair beauty_products black_dress gowns lip_stick wedding_gown sheer_dress cute_dress glam beatface lip_gloss_makeup floral_dress rubber eyebrow covergirl teen wolf Arts and Entertainment/TV illamasqua bridesmaid lip_gloss maquillaje urbandecay brushes shimmer sequinsbodycon beauty_blog ipsy nyx dressy eyebrows makeupjunkie cosmetic birchbox too_faced glossconcealer limecrime best_makeup beauty_blogger eye_shadows food Food and Drink winged_eyeliner eyemakeupeyelashes highlighter cat_eye meggy_grace_darcy makeup_tutorial wildoesthings moisturizing_lipstick maxi_dress prom_dresses pleats veilstylish peter_pan_collar wheretoget sexy_dress short_dress makeupoftheday vintage_dress beauty tips wedding gowns defined as Figure 7: Nearest neighbors of tags: a) #makeup; b) #dress XX X L= log P(tj+m |tj ). (5.1) motherfucking_cheesecake kias_one_true_love ajcinhochiminh oatmeal_with_a_fork bakingwithtanyaburr i_really_want_some_right_now erminjonathanfood sweets_for_you raspberry_macarons lovely_recipes holiday_candy vegan_muffin dessertcafe applepopbakery cinnamon_crunch avocado_pudding when_i_couldnt_taste_i_would_put_sprinkles_on_basically_everything_to_make_the_textures_more_interesting_and_bearable kakaroonsandco fruitandnut amazingcupcakes chocolate_fudge pumpkin_cinnamon_rolls oldrecipe my_dream_breakfast confectioners cookieandcream red_velvet_brownies cinnamon_raisin designercake raspberry_preserves chocolate_chip_ice_cream things_i_need_to_cook unsweetened_coconut marmellade the_best_cake valpovelveticecream sweetslover breakfadt lemon_extract vegan_cupcakes_take_over_the_world oatmealchocolatechip more_food_porn pankake caramel_cake_recipe butter_icing hot_chocolate_milk blendsbyorly kid_friendly_recipe edible_cookie_dough sandwiches_recipes cinnamon_latte instacolumbus peppermint_patties strawberris chocolate_ganache vegan_pinterest diary_of_a_stress_eatercranberry_pie meredith_video_studios_carson_s_kitchen_826 i_love_desserts dessertagram peanut_butter_oreos hocus_pocus_buns mangococonut nom_food wippedcream eclaires dark_chocolate_cake italian_bakery national_chocolate_chip_cookie_day this_midgardian_drink things_i_want_rn vegan_parfait vegan_chocolate_cake love_baking ilove2bake4you dark_chocolate_bar stawberrys smores_bars strawberryfilling somuchbutter cakerolls cupcakesniy not_macaroons chocolateweek 8_pm_food_posts lentenproject butterscotchcafe noms_by_jaime chocolate_cheesecake pumpkin_doughnuts dulce_delight 100s_and_1000s tastes_like_the_weekend cowlovesbunny glutenfreedessert mimiscookiebar candied_walnuts inrl_food apple_recipe perfection_in_a_jar blue_macaron banana_recipes featuring_fruit chocolate_mug_cake just_add_sugar this_is_foodporn coconut_cookies nycheesecake holiday_cupcakes chocolatedip plateddessert genius_recipes 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recipe_to_try baking_101 vanillachocolate dilikestobake alaskadonuts food_in_a_mug breakfastandpies sarahsfoodsection no_bake_cookies cold_treats cheeesecake raspberry_ice_cream yema_cake vegan_cream vegan_pudding n2_extreme_gelato kimobean macaronsnotmacaroons ice_cream_subscription capucchino cranberry_relish egg_custard_tartxanthan_gum chocooverload sweet_vegan fruit_sushi valentines_desserts moist_cake honeyglaze home_baked cookie_shots omg_i_need_to_make_this dessert_bars reesespeanutbutter onetsp colorful_macarons jummyinmytummy bakingislove turkishflour chochlate i_am_going_to_be_the_best_fed_college_student peanut_butter_fudge want_some_right_now homemade_nutella delicious_sweets roopabakes mint_choc amys_cooking_adventures vegetarian_appetizer chocospread c1tyup chocolate_ball heart_shaped_cookies httpswwwfacebookcomhillbillyrecipes recipe_tips raw_vegan_cake peach_crisp yummy_and_cute themed_cupcakes mycomfortfood garlic_parmesan_knots chocolatecandy icing_roses auchocolat 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moltenchocolatecake lemon_poppy_seed_muffins cinnamon_donuts toping chocchip brownie_bars choc−chip pretzelbread oreodonut chocolate_log_blog layer_cakes baking_with_peeta chai_ice_cream getdrop patisserierusselia food_ive_made yummy_yums veggieful peanut_butter_recipe cake_doughnuts heath_bars bananachocolate happilybalanced mug_cookie nitrolab wjlte frosted_cake vanilla_cheesecake ice_cream_taco cakes_and_slices chocolate_eclairs icecreamsandwhich no_churn jilanis saveyellowduck nutella_to_go cinnamon_streusel meltyblend easy_pie cheese_cakeplain lasagna_cups yummy_looking_stuff kitchen_trials yestoyum no−bake coldfood foodrecipeshq mini_oreos jam_and_cream purple_oven mint_chocolate_chips mamiaoyagi mybakes cake_blogs christmas_tree_cupcakes foodrp0001 7_layer kitchendivas chocolate desssert bakingwithbooze shortbread stickydatepudding easter_recipe chocolate_cup cheese_cream cookies_recipe caskes no−churn peanutbutterchocolatechip tions of tag t of user-specified dimensionality d, n defines the chocolate_popcorn eatngreet alpen_gold girl_cakes autumn_desserts plated_dessert candy_recipes cherrycake brownie_a_la_mode cookie_dough_truffles cookie_a_day laurenslatestnjamii spring_does_recipes foodpon sprinkle_bakes cookie_shot unbleachedwhiteflour kaysfoodfotos raspberry_and_chocolate culinaryconcoctionsbypeabody corn_cake douhgnut american_cookies popsicle_recipes sodkie_kakao quick_easy yums_and_loves fod_porn chocolateshavings dessert_lunch dssert snickers_cupcakes stuffed_cookies cookies_dough milk_with_chocolate chocolate_layer_cake chococo yumm_food nutella_frosting oreo_crust bakedgoodness for_my_butler_cafe foods_kawaii homemademacarons healthy_ish chocolate_barks breakfasr r_entree cakies salted_caramel_milkshake heaveninajar twix_bars creme_egg_brownies mcennedy peartart grilled_banana salted_caramel_popcorn tassies uitimate_food_porn cheesecake_dip wsprinkles marathon_food dessertpic nobakecookies vanilla_creme chocolate_shell chocolate_raspberry_cake misc_dinner cheese_tart mango_mousse homemadefrosting sweet_pretzels fudge_friday cake_store best_brownies peanutbutterblossoms pumpkin_2014 chispas_de_chocolate hummingbirdhigh ice_cream_pie main_food seven_layer_bars mias_domain fodporn eggnog_pancakes chocolatefoood youwillbehungry stuffed_strawberries dogoodwithfood crema_batida pumpkindonut chocolate_peanut_butter_chip_recipe cherry_pie_filling yum_d carb_heaven wagasgi tworedbowls strawberried venus_is_me caramelsyrup food_porn_pics sweet_cocoa waffle_ice_cream loaf_cake deseert food_delicious_ymmm sweetie−piesyummyblog smores_cupcake strawberry_donuts tim_vidra bicuit no_bake_cheesecake krespykreme food_tut major_cravings_now espresso_powder inatartshell cake_bites layered_dessert savory_dish happybaker food_forn shugarysweets length of the context for tag sequences, and T is the number cookieschocolate nutella_stuffed bread_experience jernejkitchen darkchocolatechips chocolate_doughnut joyofbaking cheryls 6787199279 other_sweets artisanbreads rose_frosting chocolate_ice−cream chocolate_wafer veggie_desserts carrot_cupcakes cream_cheese_brownies cooking_queue bleuchocolat cakec maple_syrup_cake food_pon snickerdoodle_cookies cookie_bowl jar_cake chocolate_cups chocozona everybody_loves_to_eat green_tea_flavor quickbread lagodons_shop turtlepie fiorgelato bake_later red_bean_ice_cream to_cook_list ice_cream_cookies donut_muffinspumpkin_chocolate_chip non−recipe mousefoodbakes slutty_brownie saintbait sortedeyecandy sidecar_doughnuts evil_ice_cream mybaking baked_onion french_crullers oreo_fudge autumn_flavors baked_cheesecake cookieporn cookie_dough_cupcakes im_getting_fat_just_looking_at_this worthgettingfat malted_chocolate red_velvet_recipes no_churn_ice_cream reipes dessert_gif custards focaccia_bread c1food cake_truffles yorgut semisweet_chocolate peach_crumble ichigo_mochi candied_fruit delicipus choclate_cake chocolate_sticks checkerboard_cake dulce_de_leche_brownies xxxfoodxxx butterfly_cakes chocolateaddiction jcocebu chocolate_gelato valentinescake dark_chocolate_chip double_chocolate_cookies deliicous pate_de_fruit food_donuts whipped_coconut_cream caramel_recipes choco_cake apple_galette buttercream_roses savory_bread misc_desserts dessert_roll multiple_recipes candy_melts choco_pops caramel_brownie summer_cake butterstudio chocolate_roll soft_baked cookies pumpkin_scone bakng crunch_cake roses_cookies chocolatem berrry mms_cookies ice_cream_topping sugar_donuts fall_desserts cook_later mounds_bar chocolate_scones apple_pancake recipe_food love_to_bake recipes_i_need_to_try lick_the_spoon mini_nutella cookie_batter foodcom chocolate_rolls pink_foods victoria_sponge_cake maple_glaze lauren_bakes chocolate_drinks foodasm chocolated coffe_cake om_noms_favorites icecream_cones caramel_apple_pie cookeis of unique tags in the vocabulary. From equation (5.2) we see chocolate_hazelnut_spread lumberjacobmartin3 sweetgasm warm_dessert eatuntildie weekend_baking gimme_some_oven cake_batter_truffles coconut_chocolate autumn_cookies ice_cream_recipes holiday_cake breafkast recipechocolate happy_marshmallow_day crepe_cakes zucre chelseasmessyapron sweets_recipe yuuuummy fay_da_bakery banana_chocolate strawberry_sauce starbucks_ice_cream loveandoliveoil butterscotch_sauce cinnamon_chips pretzel_dogs cateringdesserts deliciouss chocolatebrownies love_cupcakes gotta_make_these choco_chip_cookies thingsicooked chocogasm fruit_sorbet thecookiewriter food_decorating wltr flourless_cookies cranberry_cake cake_doughnut jamoca mini_dessert ganache tiramisu_cheesecake ferero mint_cookies dark_food coffee_cookies averiecooks cherry_crumble decadent_dessert nama_chocolate world_nutella_day cheesecake_bar recipes_included mm_s rainbow_jimmies smores_cheesecake stressbaking benandjerries cookie_cakes delsih pecan_cookies cookiesbars morellis ice_cream_chocolate white_chocolate_ganache chocolate_pecan_pie chovolate efooddiary cheesecakestuffedstrawberries cake chocolatemudcake oreo_mini gofr cookies_brownies yogurt_pops chocolate_chunk_cookies ice_cream_sammich cakeblog white_chocolate_cookies sakura_cake sunshinekitchen bear_cookies peanut_butter_bars cake_bar chad_robertson delcicious chocolate_crepe summer_baking reciperunner pecan_tartoreo_recipes pastries_recipe with_nuts i_should_make_this_sometime icingcookies ebelskivers fuwa_edit theyseemerollinandbakin crumb_topping basbousa checkerboard_cookies bombolini coffee_cakes chocolate_chunks kittykattcooks scotcheroos simplecookingchannel ambitious_kitchen sweetplantations almondcheesecakecookies kugelhopf browines urbantaphouse cupcake_blog green_frosting seeded_bread mars_kitchen choceur nutella_bread fruit_crumble chocolate_pastry coconut_cupcakes japanesecheesecake crystallized_ginger ask_about_our_vegan_options caramel_chocolate chocolate_bundt_cake sick_eats chocofudge heath_bar cupcake_decorations oh_my_gosh_yum handpie peerie_shop_cafe chip_cookies oh_my_god_this_looks_delicious chocolatebuttons lemon_macarons cheese_cakep i_want_to_try_these_so_bad mentally_obese salted_caramel ice_cream_cookie_sandwich to_eat_list vanilla_pastecukaysfudge_recipes pretty_dessert vegetarian_dessert matchacake work_snacks chocolate_fondant sweet_eats yumn sprinklesbakes oreo_frosting olive_oil_cake smore_cookies red_velvet_donut green_tea_cookies mint_chip_ice_cream lauravitale baking_from_scratch cinnamon_cookies chocloate lime_cake macaron_recipe rynagomakan pastry_recipes cacao_nib that tags that co-occur often and tags with similar contexts turtle_cookies chocolate_chip_cake ideasinfood baked_foods petite_fours crinkle_cookies banana_cookies vegan_frosting cakeinacup frosting sweetreat rice_bubbles best_desserts atsunrice oreo_ice_cream_sandwich tonsraku cake_chocolate stuffed_bread triffles sweets mabels_favorite_foods doughuts chocololate white_chocolate_cheesecake donadussifood food_making mini_chocolate_chip_cookies choco_cream craivng mypastries iambaker granitas browine donutsp chocolaye raw_cookies baking tortina cereal_treats oreo_bars individual_desserts recipe_dessert avocado_chocolate_pudding faydalicious cookiesandcups meringue_pie themoonblushbaker chocolate_desserts pumpkin_spice_smoothie cake_food smores_pie bunt_cake chocate cream_coffee blueberry_buckle and_into_my_belly pokecake doublechoc cakeball deliciouslyyum fudgeebar cakes_pies_etc buttericing things_i_bake devil_food chocolate_mousse_cake jamroll thehungryhood oreo_dessert jar_cakes best_chocolate_in_the_world truffle_cake chocolate_chip_recipe snickers_bars breakfast_bake doughnuts vegan_whipped_cream red_cupcake chocolatcake passion4baking br31 malt_powder abrowntable pieinajar strabwerry chipcoco_upload chef_delvi jelly_worms things_at_the_cafe apinchadashbakefromscratchsnickers_ice_cream cheesecake_cookies raspberry_recipes cheftiffy caramel_frosting recepi peanut_butter_mousse colorful_cupcakes tripledarkchocolate donuts_make_me_go_nuts islandcreamery brownie_cake vegan_dessert_recipes apple_pie_cookies assemblycoffee soybean_milk food_photograpy castor_sugarkare_bakes screwpine oatmealcookie girlyfood chocolate_covered_fruit peanutbutterily pecan_cake peacan small_cake hintofvanilla choclate_chip_cookies my_bakes lemon_glaze boilingbad original_cupcakes chioccolate italian_cake icecake cook_bake_eat cake_bars muffin_recipe dulche_de_leche chocolate_mouse cinnamon_recipes caramel_cookies cake_inspirations mini_cheesecake pretzel_recipe chocolate_hazelnut bakings chocolate_fingers 2_egg_whites pbs−food hot_chcolate kirbiecravings white_chocolate_macadamia_nut pumpkin_chocolate_chip_muffins double_chocolate_banana_bread chococolate when_im_bored_i_reblog_food pear_cake yummysweet marvelous_sustenance doughnut_recipes chocolatebark moelleux_au_chocolat vegan_popsicles coffee_flavor chocolate_dessert apple_cinnamon_rolls chocchipcookies ricotta_cheesecake my_cookery desserts donut_cake cookies_and_cream_cookies chocolate_buttercream canbake strawberry_recipe sliceofcake cookierecipe gallettasdecoradas choux_creme pops_recipes bakers_royale mint_brownies chocolateonchocolate tomato_tart stout_cake pretzel_roll kitkat_cake iloveonfood frosted_animal_cookies fancy_dessert fruit_desserts chocolate_chip_cookie_dough_truffles (i.e., with similar neighboring tags) will have similar vector black_icecream kitchen_dabbling tiramisu chocoate cafeblue bread_buns dessert_in_a_jar cremecheese bake_goods cold_treat peanut_butter_cupcakes chocolatedrizzle yomaro easy_cake recipe_tag_cookies chocolate_roulade savory_pies smores_brownies cake_batter_ice_cream ice_cream_pops leanne_feeds_herself recipegirl oreo_cheesecake_bars food_for_entertaining whippingcream sticky_rolls pumpkin_brownies feedingmagpies chocolatecream food−por−favor fins_not_here deliious sugar_free_recipe no_bake_recipe poshenglamgoodies jam_cookies i_am_in_with_donuts cakes_decorations krispie_treats foodorexia jezbakes caramel_tart thefoodshow recipeb bake_list pumpkin_pie_recipe ohtheplaces donugh cedarridgecafe banana_chocolate_chip caliebakery ice_creamcone cakepic millionaireshortbread iceing nussecken pankackes breakfast_bread this_is_my_pornography howtofood tv_gbbo mint_recipes chocolate_caramel chocolateroll gateux chocolate_torte mugbrownie blacksambo food_in_a_cup brownies the_caked_crusader traybake recipe_tag_chocolate eat_brekkie edible_perspective caramel_recipe find_recipe cookie_ice_cream cookiebars kronut imahkopi dragon_noms chocolatecandies savoury_pie grandpas_dinner bakedecadence adams_best browniesc craftandcake french_baking cake_mix_cookies salted_caramel_brownies resberry kitchenesse pankcake vegan_treat dessert_nachos strawberry_glaze baked_food chocolate_chip_cookie_bars 8fifteen vanillaflaca maple_bar cinnimon_roll buttermilk_recipes cookie_sandwiches samoa_cookies multivarka cupcake_bouquet belgiumchocolategourmet bakingsunday marhsmallows hazelnut_cake coconut_whipped_cream moltenchocolate chocolatechipmuffins nutella_and_banana dessert_and_food cheesecream sweetapolita bars_and_brownies somebodys_mothers_chocolate_sauce vegan_chocolate_mousse haselnut delicious_looking_food celebration_cake manifest_vegan traceysculinaryadventures deluxe_bakery candymaking mini_pie yum_omfg nhummy thanksgiving_desserts seasons_and_suppers cafefood turtlecheesecake pb_cookies need_to_cook cupackes winter_baking bakingtips blueberry_recipes pastries darkfood chocolatetruffles recipe_archive chocolate_marshmallow giantcookies cheezecake pastisserie egg_muffin revelbar cendies smores_cake molten_cake preztel pecan_pie_bars cold_dessert chococaramel biscoff_cookies jenisbook molten_chocolate newyorkcheesecake apple_cider_caramels milk_bread chcoclate homemade_candy brownieschocolate becky_cooks living_the_vegan_life pumpkin_sugar_cookies nomnomnom_b i_would_like_to_eat_this_now halloween_bark reciple choc_mint kit_kay scons raspberry_coulis french_cruller dessertfortwo food_foodporn lovely_dessert representations as learned by the word2vec model. cold_chocolate bronutsph browniecupcake chouxpastry recepe iceceam apple_pie_bites dessertfirstgirl the_best_cookies lactose_free_recipe sweet_pastries open_face_sandwichboston_cream jam_doughnuts pumpkin_loaf oatmeal_bars cookie_dough_cheesecake choclet peanut_putter easy_cookies cheesecake_brownie cupcakes_recipe floral_cupcakes buttermilk_pie sweet_snack avocado_ice_cream r_dessert donutsplain small_cakes baking_challenge foodpornphilippines lemondrizzlecake chocchips pure_food_porn pumpkin_rolls chocolite caramel_ice_cream chocoloungerd cheesecake_pie lolascafe around_the_kitchen food_porn_recipes pastel_ice_cream foodsection scrumtious caramelslice food_sweets_sweet hand_pie lattte sweetdelight butteredup pause_chocolats chocolatefruit chocolate_bar_cake wimbly_lu miniegg ferdakost helloemmasfood mocha_cake peanut_butter_frosting35food graham_cracker_crumbs chocolate_tart asian_cake keeruzs_noms touslejours caramelbeurresale poached_pears gonna_cook_this cake_vs_brownies cooking_with_friend chocolatebuttercream picnic_recipes thekitchenmccabe oreo_ice_cream_cake fatayer candy_bark chocolate_chips i_eat_nutella vegan_banana_bread banoffi mini_cinnamon_rolls fopd toddys recipec chocolate_au_pain littleandfriday peanut_butter_chip totoro_cake ferrero_rocher_cake milk_and_cookie_shots italian_dessert pumpkin_spice_cupcakes super_easy_mode chocolatebread my_food_obsession heart_shaped_waffles cinnamon_raisin_bread waffle_sandwiches dont_blog_hungry milshakes food_by_d bakingideas adorable_foods berry_crisp cookie_dough_frosting vkny peanut_butter_chocolate_chip_cookies browneyedbaker holidaycupcake coconut_ice valentines_day_dessert omg_yummmm vegan_brownie cinamon_rolls strawberry_cheescake pumpkinicecream life_love_and_sugar greenteachocolate myfoodanddrink saycheesecake nutellaislife mollysgirls sweetpizza kara_cooks tahitianvanilla chocolate_macarons national_fudge_day fondant_au_chocolat microwave_mug_cake biscuits orange_the_fruit dessert_photos powered_sugar italian_meringue chocolete cookie_mug petit_cakes peanut_butter_cookie homemadepie hardfoodporn lemon_cream akonamayfoodblog candied_nuts butterscotch_chips diy_dessert tiramisus deep_dish_cookie iced_doughnuts edible_awesomeness pastry_cream gingerbread_cupcakes cakev pf365s baked_goodies nutritious_he two_peas_and_their_pod ghost_cupcakes sorghum_flour national_caramel_day salted_caramel_cupcakes lemon_cookie would_nom chocolate_covered_pretzel yuuuuuummmm easy_recipies chicken_and_cheese onstoreshelves marengs fruitdessert strowberies family_frendly gooey_cookies smoreo food_porn_for_ts chocolate_fudge_cookies_recipe dessertpizza whatvegansbake ham_and_cheese_croissant pot_de_creme choco_chips my_name_is_yeh bakingseason caramel pasticcerie_brescia The semi-supervised skip-gram (SS-SG) model as- chocolate_chip_recipes food_taimu sliced_almonds cinnamon_scrolls shortcrust_pastry la_vie_en_rose_sweets iced_coffees chocolate_waffle doublecream datzdough macoron mascarpone_cheese gluten_free_donuts delicious_dessert dominque_ansel caras_cravings decorated_cupcakes nhamii macaron_cake delicioius lemon_icing thee_simple_foodie cookiecups new_york_super_fudge_chunk cupcake_tower cakeandbakeshow bakelikeapro short_skit_long_jacket reblogged_recipes coconut_macaroon wild_idea_buffalo_recipe_of_the_week delightful_repast cookie_swap this_looks_delicious_omg pumpkin_desserts mybakingaddiction oreobrownies meltaways annies_eats sweeys callmebettycrocker cherpumple handletheheat rice_krispy_squares allyson_kramer ideal_breakfast fruit_crisp marshmallow_recipestall_cake brownie_cupcakes polenta_cake yum_yumz no_bake_pie craving_now banana_slices cake_reference homemade_bagels pink_cookie halloween_donuts chocolatewaffle apple_cookiesnutella_french_toast lemon_poppyseed fooderific lemon_meringue_tart drizzled other_baking_stuff food_i_like_food leiansunofficialfoodblog mrspenguin earl_grey_ice_cream pumpkin_spice_cake swedish_glace alanabakes baking_tip delish−eats toogoodtoeat sticky_toffee sponge_cakes bakesession chocolate_covered_katie pateachoux the_best_of_filipino_food my_time_in_the_kitchen baci_di_dama low_faicebox_cookies cinnamon_ice_cream donuts_recipes yummy_ass_food peanut_better brownes hazelnut_chocolate pocky_cake makethisbakethis pink_oreos panna_cottas jubscupakes semisweet_chocolate_chip chocolateygoodness buttercream_cake chocolatedonuts dacquoise delicious_donuts chocolaterecipes valentines_cake culinaryblog garlic_parmesan_fries goodnessgraceous faydabakery nava_k mysokolad cookingwithray tunnel_cake cookieshot maroc_recettes these_cookies_are_the_best the_hungry_diaries bakery pastry_recipe choux_cream food_pancakes lemondrizzle fruittarts lemon_pudding naturalsweetrecipes cookie_cupcakes cinnamon_roll_cake maple_frosting food_gams vanilla_milk_chocolate dirt_cake oreo_pudding hot_dessert bryers welovedessert salted_caramel_ice_cream choclate_chip crazyicecreamlady rainbowicecream oreo_milka cinnamon_muffins cheese_cakes lemon_cream_pie nouveauraw cake_layers taiparfait salted_caramels delicouse summerdessert chocolate_crepes nowyourecooking cbtp unhealthy_food_00 caffeine_appreciation culinary_adventures_2014 pastel_foods rogalik pastel_de_chocolate chezbillysud yummy_sweetsd coconut_icecream snow_station delicious_goodness melskitchencafe chocolatw cravings_of_the_fox chocoporn savouryfood i_have_hundreds_of_videos_like_this_in_my_webcam_folder_its_unreal moar_food_pls short_bread lemon_ice_creamapiething icebox_cake crumble_cake marshmallow_ice_cream ice_cream_sandwhiches peanut_butter_cheesecake oreo_brownies soft_fruits strawberry_cakes dirt_pudding strawberry_and_creme dark_chocolate_chips fudges tempeh_salad butikpastane french_apple_tart thespatulorettekitchen foos_porn beansn2cream davidbrewsterphotography frosted_donuts the_hummingbird_bakery darkchoc dessertarian oh_these_look_so_good peanut_butter_ice_cream coconut_recipes popping_corn recipeindex avocado_pesto mousse_cake waffle_bowl i_wanna_cook_that all_from_scratch brownie_cookies vegan_cookie cupcakesbyady 2014_recipe_adventure vanilla_cookies oliver_blogging ponchik my_baking_addiction dessert_pixels chocolate_mud_cake i_really_want_to_make_these cheseecake personalizelabels heart_shaped_cake gourmet_cupcakes sumes that some tags are labeled with categories from the ugh_that_looks_good orange_cake bars_and_slices unsweetened_chocolate dessertgasm cookie_smores strawberry_rhubarb_pie cookiepizza berry_ice_cream pudding_cookies waffle_donuts ryu_food citrus_cake vegan_gingerbread food_faves strawberry_scones funfetti_cookies chocolate_bowl coffee_and_walnut_cake back40urbancafe lumberjacobmartin1 hollybrown red_velvet_cookie yummiiii week_of_menus yolofood apple_streusel oven−baked egg_blog_journey_2015 dietkillers brownie_recipes poached_pear vegan_white_chocolate pinwheel_cookies smores_recipes cat_dessert chocolatewaffles i_miss_fruit vege_food cherry_ice_cream broadswhobake vegan_cake_recipe mochi_cream koeksisters crossiants snowflake_cookies breakfast_rolls chocolate_cupcake big_yum oreobrownie kocham_czekolade berry_sauce pan_au_chocolat lemoncupcake italian_cream_cake shamallow unique_cakes lemon_pound_cake cupcakes kokosanka pancake_cake time_1_hour elys_quest_to_become_a_chubfur coconut_pie vegan_nutella pancake_love choc_chips apple_nachos microwave_cookie chocolate_chip_cookie_dough_ice_cream mini_cheesecakes marshmallow_recipe pbcupsingaporemade coffee_dessert marshmallove chocochipcheesecakecookies oh_my_god_that_looks_delicious original_cake how_to_be_a_domestic_goddess deliciousdessert new_engand_comfort_food chocolatechunks sugar_cookie_bars strawbrry schocolate foodfoodomfgfood food_photgraphy ben_jerrys_ice_cream best_icecream_ever maggiemoos pop_cake sweetgasms anytime_food whitechocolatechips coconut_bread lingsweets portenalondon soy_ice_cream grubarazzi lemoncream blue_velvet_cupcakes white_chocolate_cake mini_tart shop_cook_make bakies misc_dessert berry_compote velvetcake brownice sgbakes sweet_happinez lime_curd cake_ball sugar_powder whiped_cream eatwithrad 8_pm_food_post best_chocolate_chip_cookies ruffle_cake vanilla−says−yum mexican_wedding_cookies cream_cheese_glaze brownie_porn jummyjummy time_for_donuts chefyaritza rice_krispie hot_chocolate_mix jarcakes smith_bites _recipes food_in_a_jar croassant chocolate_shavings foodbreakfast strawberrysandcream saigoncafe spoopy_food panecake raspberry_sauce food_snack livrologosgourmet chocolate_review breadfast kim_wants_to_make_some_food not_a_vegan_but_this_looks_good yeast_rolls chocolate_salami foodlvecom hypnoticdonuts nutella_porn chocolatecookie kripsykreme cake_donut cookis cookie_bar thickened_cream eastercupcakes photosetdelicias panckcakes choocolate baking_and_decorating magic_bars lemon_muffins delicious_cakey_cake quick_dessert chocolatechips brent_hofacker alpha_beta_parking_lot coconut_extract winter_dessert lemoncupcakes mint_cupcakes creampan cookingwithchickpeas yummy_ice_cream easy_dessert_recipes mamainthekitchen baking_sweets sunflower_butter candy_cane_cookies food_oreos chocolate_peanut_butter_cheesecake caramel_cheesecake rapberries sundaybaking spritz_cookies fundue bakingwithbeck hutplace eph_cooks cocoa_market_news frosting_cupcake steawberry berry_tart sunday_sundae delightful_delectables macrofree simple_dessert s_mores gluten_free_pie butter_cream_frosting german_recipes fresh_food_friday cookingmamas fuck_that_looks_amazing francois_payard rice_crispie_treats chocolate_malt raw_ice_cream chocolate_covered_raisins rogaliki donuts_rezepte cakerecipe cocoa_gallery things_i_want_to_feed_to_cute_boys oreo_stuffed_chocolate_chip_cookies stuffed_pretzels GIT taxonomy. Next, we introduce a dummy category vec- chocolate_covered_almonds respberry farmersgirl_kitchen greek_dessert marshmalows congrats_on_ur_bread pierre_hermes gimmesomeoven foodie_recipes bunny_cookies lemonblueberry coocnut sugarpornhealthy_sweet_snacks marthasbakery matildabrewster koala_no_march oreas chocolateoverdose love_strawberry omg_these_look_delicious cobbler_recipe food_photogaphy thoughts_food 300kcal pumpkin_pie_ice_cream italian_cookies recpes apple_fries dream_breakfast asian_bakery mintchocochip easter_bread boston_c cakes_baking candied_pecans french_toast_roll_ups cupcakeschocolate cookiespread bright_food hungariansausage roasted_peaches cinema_and_spice donuts chocolate_fudge_peanut_butter_chip_bar_cookies vanilla_glaze dried_dates these_look_so_sweet the_test_kitchen sugar_pink_tag brownies_are_heaven straw_berries lemon_blueberry_cake maan_coffee these_look_heavenly these_are_so_yummy red_raspberries malted_milk_balls green_cookies strawberry_filling yumyyy sakuyas_probably_unhealthy_desserts deep_dish_pie oreo_brownie waffles_and_ice_cream salted_caramel_sauce bitofyum chocolate_peppermint plain_flour coffee_dreams ghost_cake bars_and_other_sweets cafe−diner fudgsicles worththecalories whiteplate minicookies food_that_will_make_me_fat strawberry_muffins food_waffles tempura_ice_cream whitechocolatechip burchandpurchese spring_cake after_meals dollypage cheesecake_brownies frumious_likes_food rosette_cake foodiecrush choccie minimeltsmascapone mangocrepe caramelcustard ilovesweet_ru vrecipes surprise_inside the_guitar_center_sessions imhungrybroe oh_that_looks_so_good chocoloate white_choclate cakeslice the_cookie_cup cupcakeaddict nutella easy_baking vegan_cups wo_recipe cookiewich dssert_ideas now_craving chocolate_lasagna boiling_bad cupcaketower nutellaaddict cooking_with_your_eyes strawberry_cookies let_me_eat_this kaffe_latte halloween_snack peanut_butter_chocolate man_i_need_to_try_to_make_some_of_these_things brownie_brittle thumbprintcookies genevachocolatetours sliced_banana carbolicious choc_chip french_cookies molly_yeh chihchihskitchen liquid_nitrogen_ice_cream upside−down_cake dip_recipes strawberry_roses max_brenners red_bean_mochi dulcesbocados swiss_buttercream yogurt_covered_pretzels chocolate_raspberry banana_recipe february_10_2012 kitchen_secrets mud_cake devilfoodchocolatecake these_look_tasty the_faking_foodie thisiswhyimfatseries cake_short_skirt_long_jacket color_food snakki_treats strawberrysaucespentolettando thisiswhyyourefat oh_my_god_get_in_my_mouth chocolatetime cupcakes_brisbane 1_point_recipes glutenfreedesserts longlivethenoms chocolate_lava yachi_likes donutlyfe sprinkles_u_will_always_have_a_special_place_in_my_heart orange_glaze candycriticorg julia_gartland toaster_pastries minicheesecakes reciep peanut_butter_banana almond_cookie strawberryjelly lavender_ice_cream fructose−low opal_loves_food mexican_dessert self−raising_flour foodporn_of_the_day posted_food feeding_my_baking_addiction naturally_ella hello_kitty_donut lol_my_aesthetic chocolate_cheese_cake brownies_recipe eat−like−a−hobbit tor for each node of the taxonomy, and leverage the tag con- ricotta_pancakes dessertsharing these_look_delish autumn_foods baileyanacakes old_fashioned_oats coujina125 cadburychocolate avocado_pizza yessss_nom recipe_experiment frozen_ice_cream gravy_pies_and_chicken_thighs donut_recipe must_bake smallcake butter_cookie pastry_flour _sweet_sadness_ i_could_make_this_but_thats_too_much_work chocolatedevotion fooddict lily_vanilli sugaroverdose hazelnutchocolate pure_chocolate hearty_breakfast weekend_food peerieshopcafe whaticook black_forest_gateau baking_sheet funfamilyfoods butterfinger_cups lemon_ricotta_pancakes spaggeti warm_snug_fat recipe_in_source guilt_free_dessert 6_ingredient gourmetdonuts blueberrycheese thebestcakebyneni luisarupenianphotography apple_caramel ice_cream_rose cinnamon_bun_waffles slice_of_cake mint_chocolate_ice_cream cherry_cupcakes god_that_looks_delicious chocolatecupcake fun_recipes cookie_dough_oreo fayebakes chocolatehazelnut trois_fois_par_jour raw_cheesecake blueberry_cobbler kueultah randomfood mganns_kitchen dark_chocolate pillsbury_cookies organiccake chelsea_buns fooddelicious double_chocolate chocolatechip rhaps_sets_the_stove_on_fire chocoate_ice_cream alwaysroomfordessert icing_cookies banana_nut gourmet_donuts rainbowdrops giant_cookies elsas_recipes fruit_393 coconutlovers fatties_delight haikuforbreakfast french_toast_rollups handpies bavarian_cream poke_cake did_someone_say_chocolate arcedairy icecream fancy_chocolate 8fifteensandwiches tiramisu_cake hot_chocolate_recipe owl_cupcakes peanutbutterbrownies icecreamcookie french_crepes ice_cream_stick sunday_morning_banana_pancakes smores_dip vintage_foods starving_college_student_style thehobbyist the_brunette_baker deepfrying time_40_minutes caramelcookiecrunch hazelnutspread looks_heavenly chocolate_frosting j_kenji_lopez−alt strawberryyyy carrot_muffins culinaryschooladventures photograzing molten_lava_cake easy_bread nycravings peggy_porschen quick_bread peanut_butter_jelly_sandwich purple_frosting cheeseburger_soup food_and_drink_edits japanese_cheesecake coconut_milk_ice_cream therapybaking cremadipistacchio recipe_dinner la_mia_vita_dolce marcarons texts in blog posts to jointly learn tag vectors and category vectors in the same feature space. Given such a setup, after F gure 8 Nearest tags to “Food and Dr nk/Desserts” learning the representations, every tag from the vocabulary can be categorized by simply looking up the closest category vector in the joint embedding space. 521 Training Specifically, given the labeled tags, we extend D to obtain The mode s are opt m zed us ng stochast c grad ent as- data set Dss where categories are imputed into post “sen- cent su tab e or arge-sca e prob ems However computa- tences” pi , where available. In particular, labeled tags are t on o grad ents ∇L n (5 1) and (5 3) s proport ona to the accompanied by assigned categories, and every time a vector vocabu ary s ze T wh ch may be computat ona y expens ve of a labeled central tag tj is updated to predict the surround- n pract ca tasks see ng as how T cou d eas y reach severa ing tags, the vectors of categories assigned to tj are updated m on tags As an a ternat ve we used a negat ve samp ng as well. More formally, assuming the central tag tj is la- approach 13 wh ch s gn ficant y reduces the computat ona beled with Cj of C categories in total, ζj = {c1 , . . . , cCj }, comp ex ty the semi-supervised skip-gram learns tag and category rep- The data set used dur ng the mode tra n ng compr sed 6 8 resentations by maximizing the following objective function, b on posts that conta ned tags To co ect category abe s X X X  X  or some o the tags we sorted the tags n a decreas ng order log P(tj+m |tj )+ log P(tj+m |c) . o popu ar ty and the ed tors abe ed the top ones w th one or p∈Dss tj ∈p −n≤m≤n,m6=0 c∈ζj more categor es Fo ow ng th s process we obta ned 8 400 (5.3) categor zed tags We show severa examp es n Tab e 2 The probability P(tj+m |c) of observing tag tj+m , given label The mode s were tra ned us ng a mach ne w th 96GB o c of the current tag tj , is defined using the soft-max, RAM memory and 24 cores The d mens ona ty o the em- exp(vc> vt0 j+m ) bedd ng space was set to d = 300 and the context ne gh- P(tj+m |c) = PT . (5.4) borhood s ze was set to n = 5 F na y we used 10 neg- > 0 t=1 exp(vc vt ) at ve samp es n each vector update or negat ve samp ng This procedure allows us to seamlessly incorporate labeled S m ar y to the approach n 13 most requent tags were and unlabeled data, and learn tag and category vectors in sub-samp ed dur ng the tra n ng the joint embedding space. Then, the classification of tags amounts to a simple nearest-neighbor search among the cat- 522 Inference egory vectors. In Figure 6 we show the graphical represen- When the vector representat ons o a tags are earned tation of the semi-supervised skip-gram model. we can find s m ar tags or a g ven tag by stra ght orward 7 #M croposts2016 6th Workshop on Mak ng Sense o M croposts @WWW2016 Tab e 4 Language d fferences n post tags and post text look_better_naked cassie_ho youcandothistoo two_ingredient_pancakes easiest_way_to_lose_weight fitness_meal skinny_stomach keto_krew addicted_to_fitness foodplan 28_day_habitrition_challenge ididnotgiveup college_health_blogger fitblr_friends yuliarose_ fitnessforwomen kellcastilho bridal_weight_loss get_fitn losethebelly foodprepping lose_weight_and_keep_it_off glute_exercise fitness_images_health_and_fitness healthy_on_a_budget think_thin pumpupfam unprocessedfood pro_fitness get_fit_now freshman15destruction 31_fat_loss_accelerators bodytransform dailysteps keto_adapted sparklesandspandex fat_loss_tips xenadrine sorry_for_trigger deadindesignerclothes 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fitnesscontest green_coffee_bean_diet power_bowl natural_detox project_rogers_20 juiceplusrep taxonomy we tra ned two more sem -superv sed sk p-gram F gure 9 Nearest tags to “Hea th and F tness/We ght Loss” mode s or 1) keywords rom post t t es and bod es and 2) keywords rom b og t t es and descr pt ons To tra n the Tab e 3 Prec s on and reca o categor zat on methods mode s we o owed a s m ar procedure as be ore Ed tors prov ded 4 700 categor zed keywords wh ch were used to orm tra n ng data sets or SS-SG mode earn ng Post Method Prec s on Reca keyword vectors were tra ned us ng a data set compr s ng LR-SG 0 71 0 65 N = 6 8 b on posts wh e b og t t e and descr pt on key- k-NN-SG 0 82 0 62 word vectors were tra ned us ng N = 37 1 m on b ogs SS-SG 0 85 0 63 These mode s were tra ned separate y because o the an- guage d fferences n these three doma ns between the an- guage used n post tags post text and b og t t e and de- scr pt on text To ust y our c a m n Tab e 4 we show the k-nearest ne ghbor (k-NN) searches n the ow-d mens ona nearest ne ghbors o the tag “hp” rom the tag SS-SG mode representat on space We use cos ne d stance 13 as a mea- and the word “hp” rom the post text SS-SG mode As we sure o s m ar ty To ustrate the use u ness o our ap- can see n the tab e “hp” has two d fferent mean ngs n post proach examp es o s m ar tags to the tags #makeup and tags and post text doma ns re err ng to “Harry Potter” and #dress are shown n F gure 7 where we can see that se- “Hew ett-Packard” respect ve y mant ca y re ated tags are grouped n the same part o the To find the most confident keywords or each category we embedd ng space ca cu ated the cos ne d stances between keyword vectors and S m ar y we can find the most ke y category or any tag category vectors rom the vocabu ary We retr eved 184 000 by find ng the nearest category n the vector space To pro- text b og keywords w th a cos ne d stance o 0 7 or h gher duce a confident set o categor zed tags we retr eved on y We repeated the same procedure or keywords rom b og tags w th a cos ne d stance o 0 7 or h gher to the corre- t t es and descr pt ons resu t ng n 173 000 categor zed key- spond ng category vectors Th s thresho d was obta ned words through ed tor a eva uat on o the resu ts In tota more 53 Forming interest segments than 380 000 tags were confident y categor zed nto one or more categor es We show examp es o categor zed tags or The goa o the task o nterest pred ct on s to dent y the categor es “Food and Dr nk/Desserts and Bak ng” and groups o users w th an nterest n certa n top cs such as “Hea th and F tness/We ght Loss” n F gures 8 and 9 re- mus c trave cook ng or books n order to a ow advert sers spect ve y w th tag s zes n descend ng order o re evance to target the Tumb r aud ence accord ng to the r nterests A demonstrat on v deo o our tag categor zat on too Be ow we descr be the method or pred ct ng user nterests s ava ab e on ne at http://youtu.be/ygn5oUBydfM wh ch was used n th s study In part cu ar a ter we obta ned categor zed tags and key- 523 Evaluation words the nterest score or user u n the k-th category at t me t was ca cu ated as In order to quant y the benefits o our approach we eva - X X uated the method by exc ud ng a random 1 000 tags rom u ca =k = α − ac wkw I(kw s o c ass k) the ed tor a y abe ed set and tra n ng the mode us ng the ac ∈A kw∈ac rema n ng 7 400 abe ed tags We compared the SS-SG c as- (5 5) s ficat on to the state-o -the-art og st c regress on (LR) and where A s the set o a act v t es o user u wkw s the k-NN tra ned on the vectors earned by the or g na SG va ue o the keyword eature (e g the post conta ns two mode For LR c ass ficat on (we re er to the method as LR- ment ons o the keyword “shak ra” n the same t me stamp SG) we tra ned one c ass fier per nterest category wh e n then the va ue s equa to 2 as exp a ned n Sect on 4 2) k-NN (we re er to the method as k-NN-SG) or each test wh e the nd cator unct on I( ) returns 1 the keyword 8 #M croposts2016 6th Workshop on Mak ng Sense o M croposts @WWW2016 Table 5: Examples of interest inference based on categorized user features User Inferred interest User profile user 1 Arts and Entertainment/Movies tag:{spoilers:30, shrek:18, hercules:12, cinderella:3, hobbit:123, hulk:21, pokemon:7, thor:58, . . . disney:500, tarzan:8, marvel:385, wolverine:21, twilight:2, pixar:87, godzilla:1, x-men:53, . . . pocahontas:4, avengers:134} txt:{aladdin:28, batman:10, bambi:12, movies:100} desc:{oscar:1, animation:12, comedy:1, movie:1, dvd:1} user 2 Style and Fashion tag:{ womensfashion:110, curls:6, fashiondiaries:133, redhair:2, menswear:125, chanel:4 . . . springfashion:50, style:132, streetstyle:132, hairstylist:134, dapper:3, mensfashion:124} txt:{fashion:108} user 3 Food and Drink tag:{food:11, dessert:4 , soup:1, brunch:1, fruit:2, chicken:3, smoothie:1, cake:2, breakfast:2, . . . ginger:2, salad:5, avocado:1} txt:{food:16, meals:6} follows:{user4542:1, user84852:1, user9332:1, user4524424:1 } user 4 Home and Garden tag:{daisies:2, kitchen:20, chair:3, art:81, outdoor:20, chandelier:12, lamp:8, window:2, bath:1 . . . floral:17, home:3, wildflowers:1, flowers:102, interior:201, tree:1, flower:49, table:1, stairs:2, . . . bedroom:56, wood:2, bathroom:26} txt:{garden:32, interior:17, home:41} user 5 Automotive/Motorcycles tag:{cars:24, ride:9, vehicle:22, riding:8, road:18} txt:{bike:8, motorcycle:10, riding:5, ride:9, road:10, vehicle:18, bikes:6, bicycle:2, scooter:1} extracted from an activity is of class k, and 0 otherwise. Table 6: A/B test results on 10% of user population In addition, we used the time stamp tact , representing the day in which the activity happened, to exponentially decay Campaign Control Targeted less recent activities to account for passing interest (we used Home and Garden − +9.71% α = 0.99 in our experiments). Note that the set Ai , in Style & Fashion − +42.53% addition to the user’s original content, also included posts Sports/Outdoor Sports − +19.86% reblogged by user ui . Arts & Enter./Television − +24.37% The value of uti,cat=k represents an exponentially time- Arts & Enter./Video Games − +19.02% decayed count of all the activities in the k-th category. To Pets/Dogs − +27.21% effectively store the user profile for interest targeting, instead Arts & Entertainment 1 − +9.08% of storing all possible activities and their time stamps, we Arts & Entertainment 2 − +6.54% maintain a decayed sum of the activities and update the uti,cat=k daily. Using this approach, we are able to qualify top K users in posts created by the b-th blog were liked ten times, then the each category by sorting the interest score uti,cat=k . Depend- value was set to 10; if a user followed the b-th blog, then ing on the advertiser’s goals and the category, the choice of the value was set to 1), while the indicator function I(·) K varies from campaign to campaign. We note that a sin- returns 1 if the blog is of class k, and 0 otherwise. Similarly gle user can be qualified into one or more interest categories to other activities, we applied the exponential decay to the (e.g., a user can be categorized in “Sport”, “Sport/Basketball”, sum, based on the time stamps of follow and like actions. and “Health and Nutrition/Vitamins” at the same time), We have observed that additional signals, in the form of and, when the system was deployed, each user was assigned follow and like engagement with frequent bloggers, increase to 13 categories on average. An example of user profiles our segment sizes, making it possible to efficiently target a qualified into certain categories is given in Table 5. greater number of users. 5.3.1 Leveraging the follower graph 5.4 Results To be able to target Tumblr users who do not create In order to evaluate the generated user interest segments, much content, but who actively follow and engage with other we performed online A/B testing and worked with several blogs, we leverage the follower graph to create additional advertisers who ran concurrent interest-targeted and untar- categorized features. Using equation 5.5 we can identify fre- geted campaigns. We tracked user engagement with their quent bloggers in certain interest categories by focusing on ads in terms of sponsored post likes, reblogs and follows, a small percentage of users with a maximum ui,cat=k . Fol- and show the results for 8 targeting campaigns in Table 6. lowing and liking posts created by social influencers in the We observed an average increase of 20% in user engagement k-th category serves as additional evidence of one’s interest (aggregate of 3 metrics) with sponsored posts in comparison in that category. to untargeted campaigns. This performance result repre- In each interest category, we label the 5% of users with sents a significant improvement over the baseline approach. the highest number of activities in that category as frequent bloggers. Next, we update the interest score of all users ui in the k-th category, in the following manner 6. GENDER PREDICTION X X (t−t ) In this section, we explain the details of our gender pre- uti,cat=k + = α eng weng I(b is of class k), diction model, based on the user profiles described in the b∈Fi eng∈b previous sections. We first describe the generation process (5.6) of a golden set of labeled users, which is used to train a where Fi is a set of all frequent blogs followed by user ui , predictive model that generalizes well on the remaining un- eng are all engagements with the b-th blog, i.e. likes or labeled users. This is followed by the model’s description follow actions, along with their weights weng (e.g., if the and a discussion of the results. 9 · #Microposts2016 · 6th Workshop on Making Sense of Microposts · @WWW2016 Table 7: Matching names in blog description (* represents Table 8: Accuracy of gender model on hold-out set matched name; 564K female and 395K male users found) Gender Precision Recall regex count female 0.806 0.838 my name is * 783,564 male 0.794 0.689 my name’s * 291,811 me llamo * 47,663 the name’s * 38,065 Table 9: Editorial evaluation of random user predictions mi nombre es * 9,751 mi chiamo * 9,181 Class Prediction Correct Wrong Not sure mein name ist * 1,025 female 429 4 298 meu nome e * 512 male 144 5 127 mon nom est * 215 mio nome e * 185 function of input x, passed through a sigmoidal function, 6.1 Collecting ground-truth labels P(y = 1|x) = f (x, w) = 1 , (6.1) 1 + exp(−xT w) In order to train the machine learning method for gender prediction, in addition to user profiles, we also require la- and P(y = 0|x) = 1 − P(y = 1|x). To estimate the parame- bels that present the ground truth (i.e., “male” or “female”). ters w, we minimize the following loss function, However, Tumblr does not collect gender information when N users sign-up, leaving open the question of how to obtain 1 X 2 min yi − f (xi , w) + λkwk1 , (6.2) such data. w∈RK N i=1 To address this problem, we proposed to leverage highly informative blog description data in order to infer user gen- where hyper-parameter λ controls the `1 -regularization, in- der information. In particular, very often users declare their troduced to induce sparsity in the parameter vector and re- name in the blog description, as illustrated in Figure 1. To duce the feature space to a subset of features that are the extract the users’ declared names, we used several regular most predictive. For data sets with a large number of fea- expression rules that we found to result in very high preci- tures, as we have in our use case, it is common that many sion. The obtained results from a large set of name-matching features are not useful for producing the desired learning regular expressions were editorially tested for quality. It was result. For this reason, the `1 -regularization was a critical found that regular expressions reported in Table 7 yielded part of our training procedure. In addition, we experimen- the most reliable extracted names (valid names were ex- tally observed that the model generalizes better when we tracted in more than 95% of the cases). Next, in order trained an initial model with `1 -regularization to find which to generate the gender ground truth, we used the US cen- features have non-zero weight, and then do another round sus data of popular baby names10 from year 1880 to 2013 of training without `1 -regularization, by only using features to create a “name → gender” mapping. Seeing as how cer- with non-zero weights from the first round to learn a better tain names are given to both males and females, we used classifier. the empirical counts of babies with certain names from cen- Given a trained logistic regression model, the posterior sus data to generate the labels. More specifically, we used class probabilities are estimated as f (xi , w) ∈ [0, 1]. Then, male/female empirical ratios as soft labels, with 1 indicating the classification predictions are made by thresholding, as 100% confidence in a male and 0 indicating 100% confidence ŷi = sign(f (xi , w) − θ), where threshold θ is set between 0 in a female name. and 1 to ensure the desired precision and recall according to specific advertisers requirements. 6.2 Proposed approach 6.3 Results Let Dg = {(xi , yi ), i = 1, ..., N } denote our gender data To evaluate the accuracy of our gender prediction frame- set, where N is the total number of labeled users, xi is the work, we trained a logistic regression model on 70% of the K-dimensional user feature vector generated from the user golden set and tested on the remaining 30%. We used the profiles, and yi ∈ [0, 1] is the user label (real-valued number, Vowpal Wabbit [10] implementation on Hadoop to train the ranging from 0 to 1). The feature vectors were generated model. To illustrate the performance of our gender classi- from the user profiles described in Section 4.2, by disregard- fier, the performance results in terms of precision and recall ing time stamps (due to the fact that, unlike the users’ in- measures are presented in Table 8. The threshold value θ terests, their gender does not fluctuate), and directly using was set to a value which ensured precision of 0.8. the feature counts as values. To handle large counts, we In addition to evaluation on the hold-out set, we also edi- normalized the counts by applying log transformation: as- torially evaluated gender predictions on the unlabeled data suming that the count is x, we replace the count by the value set of user profiles. We randomly picked 1,007 gender pre- log(1 + x). dictions from the population of 64.1 million users and asked Our goal is to learn a gender-predictive model, f : x → editors to visit their profiles and verify their gender. They y. As a classification model, we used logistic regression, were instructed to mark our predictions as “correct”, “incor- parameterized by weight vector w. We assume that the rect”, or “not sure”. The “not sure” grade is to be used when posterior gender probabilities can be estimated as a linear the visual inspection of a profile is inconclusive, as we found was often the case. The editorial judgment came back with 10 www.ssa.gov/oact/babynames/limits.html 573 “correct” (429 females and 144 males), 9 “incorrect”, and 10 · #Microposts2016 · 6th Workshop on Making Sense of Microposts · @WWW2016 425 “not sure” grades (see Table 9). The fact that there are [4] F. Bonchi, R. Perego, F. Silvestri, H. Vahabi, and so many “not sure” grades indicates that in many cases it R. Venturini. Efficient query recommendations in the is hard to infer the gender even after manual efforts, fur- long tail via center-piece subgraphs. In Proceedings of ther indicating the benefits of the proposed approach and the 35th International ACM SIGIR Conference on its superior performance in comparison to humans. Finally, Research and Development in Information Retrieval, we retrained the model with 100% of the golden set and SIGIR ’12, pages 345–354, New York, NY, USA, 2012. deployed it in Yahoo production systems. ACM. A demonstration video of the most predictive tags [5] A. Z. Broder. Computational advertising and in each gender group is available online at https://www. recommender systems. In Proceedings of the ACM youtube.com/watch?v=jXGJ0TpOlhg. conference on Recommender systems, pages 1–2. ACM, 2008. 7. DEPLOYED SYSTEM [6] Y. Chang, L. Tang, Y. Inagaki, and Y. Liu. What is Due to the rapid growth of Tumblr and the large number tumblr: A statistical overview and comparison. 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