=Paper= {{Paper |id=Vol-1609/16091197 |storemode=property |title=Cultural micro-blog Contextualization 2016 Workshop Overview: data and pilot tasks |pdfUrl=https://ceur-ws.org/Vol-1609/16091197.pdf |volume=Vol-1609 |authors=Liana Ermakova,Lorraine Goeuriot,Josiane Mothe,Philippe Mulhem,Jian-Yun Nie,Eric Sanjuan |dblpUrl=https://dblp.org/rec/conf/clef/ErmakovaGMMNS16 }} ==Cultural micro-blog Contextualization 2016 Workshop Overview: data and pilot tasks== https://ceur-ws.org/Vol-1609/16091197.pdf
      Cultural micro-blog Contextualization 2016
       Workshop Overview: data and pilot tasks

    Liana Ermakova1 , Lorraine Goeuriot2 , Josiane Mothe1 , Philippe Mulhem2 ,
                       Jian-Yun Nie3 , and Eric SanJuan4
           1
               IRIT, UMR5505 CNRS, ESPE, Université de Toulouse, France
                        2
                            LIG, Université de Grenoble, France
                    3
                      RALI, Université de Montréal, Québec, Canada
                          4
                             LIA, Université d’Avignon, France
                josiane.mothe@irit.fr eric.sanjuan@univ-avignon.fr



        Abstract. CLEF Cultural micro-blog Contextualization Workshop is
        aiming at providing the research community with data sets to gather,
        organize and deliver relevant social data related to events generating a
        large number of micro-blog posts and web documents. It is also devoted
        to discussing tasks to be run from this data set and that could serve
        applications.


1     Introduction

Festivals are gaining an increasing success and some of them, such as Cannes,
Edinburgh or Avignon, produce a significant activity on the Web. This Work-
Shop proposes to develop access methods for the contents generated during and
around the festivals to better understand the festival practices [1]. The underly-
ing scientific problems concern both IR and humanities. This WorkShop focuses
on two axes: the contextualization of the data collected on the Web and the
search of content captured or produced by internet users [2].
    For its first edition, it gives access for registered participants to a massive
collection of microblogs and related urls5 [3].
    In this overview we report the main tentative tasks that have been suggested
to be discussed and experimented during the workshop. First §2 we introduce the
contextualization task based on the Wikipedia. Then in §3 we discuss a possible
microblog search task over a long time period. In §4 a timeline search task over
several festivals is proposed.


2     Microblog Contextualization based on Wikipedia

This initial task aimed at generating a short summary providing the background
information of a tweet to help a user to understand it following[4]. Given a
microblog announcing some cultural event, participants have to provide a short
5
    All resources are available online:http://cmc.talne.eu
summary extracted from Wikipedia that provides -extensive -background about
this event. The summary must contain some context information about the event
in order to help answering questions of the form ”what is this tweet about?”
using a recent cleaned dump of Wikipedia. The context should take the form of
a readable summary, not exceeding 500 words, composed of passages from the
provided Wikipedia corpus.
    Any open access resource could be used in addition to the data provided to
participants subject to describing it and providing a valid URL.


2.1   Datasets

A restricted set of public micro-blogs in English were collected from a set of
public on Twitter, all related to the keyword festival. The micro-blogs are in
UTF8 csv format with various fields. In this task, the tweets do not contain
URL. The other suggested tasks would use additional information.
    Unlike tweets, Wikipedia is under Creative Common license, and its contents
can be used to contextualize tweets or to build complex queries referring to
Wikipedia entities. We extracted from Wikipedia an average of 10 million XML
documents per year since 2012 in the four main twitter languages:- en, es, fr and
pt. -These documents reproduce in an easy-to-use XML structure the contents
of the main Wikipedia pages: title, abstract, section and subsections as well as
Wikipedia internal links. Other contents such as images, footnotes and external
links are stripped out in order to obtain a corpus easy to process by standard
NLP tools. By comparing contents over the years, it is possible to detect long
term trends


2.2   Evaluation

Following [5] the summaries would be evaluated according to informativeness
and readability.
    Informativeness is the way they overlap with relevant passages (number of
them, vocabulary and bi-grams included or missing). For each tweet, all passages
from all participants will be merged and displayed to the assessor in alphabetical
order. Therefore, each passages informativeness will be evaluated independently
from others, even in the same summary. Assessors will only have to provide a
binary judgment on whether the passage is worth appearing in a summary on
the topic, or not.
    Readability can only be accurately assessed by humans. A small panel of
scholars in humanities will have to evaluate readability for a pool of summaries
using on an online web interface. Each summary consists of a set of passages
and for each passage, assessors will have to tick four kinds of check boxes:

 – Syntax (S): tick the box if the passage contains a syntactic problem (bad
   segmentation for example),
 – Anaphora (A): tick the box if the passage contains an unsolved anaphora,
 – Redundancy (R): tick the box if the passage contains redundant information,
   i.e. information that has already been given in a previous passage,
 – Trash (T): tick the box if the passage does not make any sense in its context
   (i.e. after reading the previous passages). These passages must then be con-
   sidered as trashed, and the readability of following passages must be assessed
   as if these passages were not present.


3     Cultural MicroBlog Search based on WikiPedia entities
Given a cultural entity as a set of WikiPedia pages (typically a set of places to
visit, artists to see on stage, festivals of interest etc.), the proposed task would
be to provide a double extensive summary of relevant microblogs from insiders
and outsiders. This task will involved two sub-tasks:
Task 2a: Retrieval of relevant microblogs for an entity (described by its wikipedia
page)
Task 2b: Summarization of the most informative tweets (and comparison to
manually built summaries)

3.1    Micro-blog collection
The document collection is provided to registered participants by ANR GAFES6
project and consists in a pool of more than 50M unique micro-blogs from different
sources with their meta-information as well as ground truth for the evaluation.
    The micro-blog collection contains among other sources, all public posts on
Twitter using the keyword festival since June 2015. These micro-blogs are col-
lected using private archive service based on streaming API7 . The average of
unique micro-blog posts (i.e. without re-twitts) between June and September is
2, 616, 008 per month.The total number of collected micro-blog posts after one
year (from May 2015 to May 2016) is 50, 490, 815 (24, 684, 975 without re-posts).
    These micro-blog posts are available online on a relational database with
associated fields, among them 12 are listed in Table 1. The “Comments” row in
Table 1 gives some figures about the existing corpus.
    Because of privacy issues, they cannot be publicly released but can be an-
alyzed inside the organization that purchases these archives and among col-
laborators under privacy agreement. CLEF 2016 CMC Workshop provided this
opportunity to share this data among academic participants. These archives can
be indexed, analyzed and general results acquired from them can be published
without restriction.

3.2    Linked web pages
66% of the collected micro-blog posts contain Twitter t.co compressed URLs.
Sometimes these URLs refer to other online services like adf.ly, cur.lv, dlvr.it,
6
    http://anr-gafes.univ-avignon.fr/demo.html
7
    https://dev.twitter.com/streaming/public
      Name                     Description               Comments
       text                  text of the twitt           99% of the twitts contain a non empty text
                                                         66% contain an external compressed URL
      from user           author of twitt (string)       62, 105 organizations among 11, 928, 952 users.
          id              unique id of micro-blog        total so far: 50, 490, 815 posts.
 iso language code         encoding of the twitt         the most frequent tags: en (57%), es (15%),
                                                         fr (6%) and pt (5%).
        source      interface used for posting the twitt frequent tags: Twitter Web Client (16%)
                                                         iPhone and Twitterfeed clients (11% each).
     
                    Table 1. Fields of the micro-blog posts collection.



ow.ly, thenews.uni.me and twrr.co.vu that hide the real URL. We used the spi-
der mode to get the real URL, this process can require several DNS requests.
The number of unique uncompressed urls collected in one year is 11, 580, 788
from 641, 042 distinct domains. Most frequent domains are: twitter.com (23%),
www.facebook.com (5.7%), www.instagram.com (5.0%), www.youtube.com (4.5%),
item.ticketcamp.net (1.1%) and g1.globo.com (1%)


4     TimeLine illustration based on Microblogs

The goal of this task is to link the events of a given festival program to related
microblog posts. Such information is useful for attendees of festivals, for people
that are interested in knowing what happens in a festival, and for organizers to
get feedback[6].
    Microblog posts are provided with their timestamps, which are crucial as
a basis for the requested linking. However, such timestamps must be use with
care: they do not necessarily give accurate enough information (for instance in
the case of parallel sessions), or might even generate perturbations (microblogs
about one event may be posted before, during, or after the actual event).
    Participants would be required to provide, for each event of the program, the
10 best tweets based on their relevance and diversity. In this task, diversity is a
must because retrieving several times the same post is not beneficial in our case.


4.1   Data

Participants for this task would use a subset of the microblogs collection, match-
ing the months the targeted festivals were organized at (July and December
2015).
    In its tentative form, Festival programmes are provided in French: Two
French music festivals have been selected: the festival des vieilles charrues and
the transmusicales de Rennes. The timelines provided are selected subset of each
festival program: the organizers selected a subset of the whole festival program
(for each stage and time, list of artists playing).
    The participants would be free to use any additional data to provide results:
social (popularity, ) or not (knowledge bases, ); it should be described in the
related paper and specified when submitting the runs.

4.2   Evaluation
The evaluation would be carried out on selected parts of the program chosen by
the task organizers depending on the number of relevant tweets per event. The
evaluation measures planned would be recall/precision based. Several types of
runs will be proposed: time-only, content-only, time&content.


5     Conclusion
Cultural Microblog Contextualization CLEF 2016 WorkShop aims at developing
processing methods for social media mining. Our focus is around festivals that
are organized or that have a large presence on social media. Micro-blogs linked
to an event make a dense, rich but very noisy corpus. Content is often imprecise,
duplicate or non-informative.
    We also envisage to provide an extra corpus of Images related to cultural
festivals in the world. This access would allow researchers in IR and NLP to ex-
periment a broad variety of multilingual microblog search techniques (WikiPedia
entity search, and automatic summarization). Extensive textual references would
be provided by scholars in humanities involved in the ANR GAFES project.


References
1. Heijnen, J., de Reuver, M., Bouwman, H., Warnier, M., Horlings, H. : Social Me-
   dia Data Relevant for Measuring Key Performance Indicators? A Content Analysis
   Approach. In Co-created Effective, Agile, and Trusted eServices, Lecture Notes in
   Business Information Processing, Vol. 155, Springer Berlin Heidelberg, 74–84, 2013.
2. Rui, H., Whinston, A. : Designing a Social-broadcasting-based Business Intelligence
   System, ACM Trans. Manage. Inf. Syst., ACM, New York, NY, USA, 2(4):1–19,
   2011.
3. Liu, I., Cheung, C., Lee, M. : Understanding Twitter Usage: What Drive People
   Continue to twitt., PACIS, 92, 2010.
4. SanJuan, E., Bellot, P, Moriceau, V., Tannier, X., Overview of the INEX 2010 Ques-
   tion Answering Track (QA@INEX), in: S. Geva, J. Kamps, R. Schenkel, A. Trotman
   (Eds.), INEX, Vol. 6932 of Lecture Notes in Computer Science, Springer, 2010, pp.
   269–281.
5. Bellot, P., Moriceau, V., Mothe, J., Tannier, X., SanJuan, E. : INEX Tweet Contex-
   tualization task: Evaluation, results and lesson learned in Information Processing &
   Management, in press, 2016.
6. Leskovec, J., Backstrom, L., Kleinberg, J. : Meme-tracking and the dynamics of
   the news cycle. In Proceedings of the 15th ACM SIGKDD international conference
   on Knowledge discovery and data mining (KDD ’09). ACM, New York, NY, USA,
   497–506, 2009.