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https://ceur-ws.org/Vol-1619/preface.pdf
25th International Joint Conference on
Artificial Intelligence
New York City, USA, 9th-15th July, 2016
Proceedings of the 4th Workshop on
Sentiment Analysis where AI meets Psychology
(SAAIP 2016)
New York City, USA, 10th July, 2016
SAAIP 2016
Volume Editors
Sivaji Bandyopadhyay
Department of Computer Science and Engineering,
Jadavpur University, Kolkata - 700032, India.
E-mail: sivaji cse ju@yahoo.com
Dipankar Das
Department of Computer Science and Engineering,
Jadavpur University, Kolkata - 700032, India.
E-mail: dipankar.dipnil2005@gmail.com
Erik Cambria
School of Computer Engineering,
Nanyang Technological University, Singapore 639798.
E-mail: cambria@ntu.edu.sg
Braja Gopal Patra
Department of Computer Science and Engineering,
Jadavpur University, Kolkata - 700032, India.
E-mail: brajagopal.cse@gmail.com
Publisher
CEUR Workshop Proceedings
http://ceur-ws.org/Vol-1619
ISSN 1613-0073
Copyright c 2016 for the individual papers by the papers’ authors. Copying permitted for
private and academic purposes. This volume is published and copyrighted by its editors.
SAAIP 2016
Preface
In recent times, research activities in the areas of Opinion, Sentiment, Emotion and/or Mood
in natural language texts, speech, music and other media have become the mainstream research
under the umbrella of subjectivity analysis and affective computing. These tasks are considered
vital from various academic and commercial perspectives since a decade. The popularity of the
Internet and the rapid expansion of social media have made available online a variety of user
generated contents. However, the major challenges are how to process the user generated
contents such as texts, audio and images and how to organize them in some meaningful ways.
The common interest areas where Artificial Intelligence (AI) meets sentiment analysis can
be viewed from four aspects of the problem and the aspects can be grouped as Object identi-
fication, Feature extraction, Orientation classification and Integration. The existing reported
solutions or available systems are still far from being perfect or fail to meet the satisfaction level
of the end users. The main issue may be that there are many conceptual rules that govern sen-
timent and there are even more clues (possibly unlimited) that can convey these concepts from
realization to verbalization of a human being. Human psychology may provide the unrevealed
clues and govern the sentiment realization. The important issues that need attention include
how various psychological phenomena can be explained in computational terms and which AI
concepts and computational methodologies will be proved as the most useful ingredients from
the psychologist’s point of view.
Sentiment analysis from natural language texts is a multifaceted and multidisciplinary prob-
lem. Research efforts are being carried out for identification of positive or negative polarity of
the evaluative text and also for the development of devices that recognize human affect, display
and model emotions from textual contents. Identifying strength of sentiment in figurative texts
or aspects and categories from the reviews, detecting stance from the tweet data, identifying
the psychological condition of persons from chat even detecting sentiment in clinical texts and
the moods from music etc. are the recent trends in the field of sentiment analysis.
Mood analysis from music is an emerging area in Music Information Retrieval (MIR). The
popularity of downloading and purchasing of music from online music shops have increased.
Similarly, with rapid evolvement of technology, music is just a few clicks away, on almost any
personal gadget be it computers, portable music players, or smart phones. This fact underlines
the importance of developing an automated process for its organization, management, search
as well as generation of playlists and various other music related applications. Recently, MIR
based on emotions or moods has attracted the researchers from all over the world because of
its highly motivated implications in human computer interactions.
In addition to Question Answering or Information Retrieval systems, Topic-sentiment anal-
ysis is being applied as a new research method for mass opinion estimation (e.g., reliability,
validity, sample bias), psychiatric treatment, corporate reputation measurement, political ori-
entation categorization, stock market prediction, customer preference or public opinion study
and so on. Techniques from Artificial Intelligence play the important roles in these tasks. In
recent times, regular research papers continue to be published in reputed conferences like ACL,
NAACL, EMNLP, COLING, IJCNLP, CICLing, EACL etc. The Sentiment Analysis Sympo-
siums are also drawing the attention of the research communities from every nook of the world.
There has been an increasing number of efforts in shared tasks such as SemEval 2007 Task:
Affective Text, SemEval 2013-2016 Task: Sentiment Analysis on Twitter, SemEval 2014-2016:
Aspect-Based Sentiment Analysis, SemEval 2015: Sentiment Analysis of Figurative Language
in Twitter, SemEval 2015: CLIPEval Implicit Polarity of Events, SemEval 2016: Detecting
Stance in Tweets, SemEval 2015-2016: Clinical TempEval, TAC 2008 Opinion Summarization
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SAAIP 2016
task, TREC-BLOG tracks since 2006, and relevant NTCIR tracks since 6th NTCIR that aimed
to focus on different issues of opinion and emotion analysis. Research activities on Sentiment
Analysis have been performed in several languages other than English. The shared task Sen-
timent Analysis in Indian Languages (SAIL) Tweets in 2015 has been organized to detect the
sentiment from Bengali, Hindi and Telugu tweets. The shared task Aspect-Based Sentiment
Analysis in SemEval 2016 has also targeted sentiment analysis in the languages like Arabic, Chi-
nese, Dutch, French, Russian, Spanish and Turkish including English. Some of the important
names e.g., MediEval: Emotion in Music and MIREX: Audio Music Mood Classification are
the evaluation campaigns for the mood classification from music using audio. The 16th Interna-
tional Society for Music Information Retrieval (ISMIR) is one of the most reputed conferences
in the field of music and has published many papers related to music mood.
Several communities from sentiment analysis have engaged themselves to conduct relevant
conferences, e.g., 6th Affective Computing and Intelligent Interfaces (ACII), 5th Annual Con-
ference Behavioural Models & Sentiment Analysis Applied to Finance in 2015, symposiums
such as Sentiment Analysis Symposium in 2015, and workshops such as Sentiment Analysis
Innovation, “Sentiment and Subjectivity in Text” collocated with COLING-ACL 2006, “Sen-
timent Analysis – Emotion, Metaphor, Ontology and Terminology (EMOT)” in LREC 2008,
Opinion Mining and Sentiment Analysis (WOMSA) 2009, “Topic-Sentiment Analysis for Mass
Opinion Measurement (TSA)” in CIKM 2009, “Computational Approaches to Analysis and
Generation of Emotion in Text” in NAACL 2010, 6th Workshop on Computational Approaches
to Subjectivity and Sentiment Analysis (WASSA) in EMNLP 2015, FLAIRS 2011 special track
on “Affect Computing”, 5th Sentiment Elicitation from Natural Text for Information Retrieval
and Extraction (SENTIRE 2015), 5th Workshop on EMOTION, SOCIAL SIGNAL, SENTI-
MENT AND LINKED OPEN DATA (ESLOD 2014) in the satellite of LREC 2014, “Practice
and Theory of Opinion Mining and Sentiment Analysis” in conjunction with KONVENS-2012
(PATHOS-2012), Intelligent Approaches applied to Sentiment Mining and Emotion Analysis
(WISMEA, 2012), Socio-Affective Computing, Emotion and Sentiment in Social and Expressive
Media, workshop on “Issues of Sentiment Discovery and Opinion Mining (WISDOM, 2012)”,
and a bunch of special sessions like Sentiment Analysis for Asian Languages (SAAL, 2012),
Brain Inspired Natural Language Processing (BINLP, 2012), Advances in Cognitive and Emo-
tional Information Processing (ACEIP, 2012), Language Technologies for Indian Social Media
in 2014 and so on.
Since our previous three workshops in conjunction with the International Joint Conference
on NLP (IJCNLP) in Chiang Mai, Thailand during Nov. 7-13, 2011, International Conference
on Computational Linguistics (COLING) in Mumbai, India during Dec. 8-15, 2012 and with the
International Joint Conference on NLP (IJCNLP) in Nagoya, Japan during the period October
14-18, 2013 were quite successful (with 20, 14, and 10 submissions and more than 30 participants
from many countries). Prof. Eduard Hovy and Prof. James Martin were the keynote speakers
for the first and second versions of this workshop, respectively. Inspired by the objectives we
aimed at in the first three editions of the workshop, the warm responses and feedbacks we
received from the participants and attendees and the final outcome, the purpose of the 4th
edition of the Workshop on Sentiment Analysis where AI meets Psychology (SAAIP 2016) in
conjunction with International Joint Conference on Artificial Intelligence (IJCAI) 2016, is to
create a framework for presenting and discussing the challenges related to sentiment, opinion,
emotion, and mood analysis in the ground of NLP. This workshop also aims to bring together
the researchers in multiple disciplines such as computer science, psychology, cognitive science,
social science and many more who are interested in developing next generation machines that
can recognize and respond to the sentimental states of the human users. This time we received
ii
SAAIP 2016
twelve submissions and finally eight papers have been accepted.
The keynote presented by Professor Björn Schuller is on seven essential principles to make
multimodal sentiment analysis that works in the wild. A web-based interactive speech emotion
classification system (WISE) that allows users to upload speech data and automatically classify
the emotions was provided by Sefik Emre Eskimez, Melissa Sturge-Appley, Zhiyao Duan and
Wendi Heinzelman.
Jasy Liew Suet Yan, Howard R. Turtle presented a work where a set of 48 emotion categories
is discovered for the first time inductively from 5,553 annotated tweets through a small-scale
content analysis by trained or expert annotators and then a set of 28 emotion categories was
refined and tested to find out how representative they are on a larger set of 10,000 tweets
obtained through crowd sourcing. While the most existing work in domain adaptation has
focused on feature-based and/or instance-based adaptation methods, Bo Wang Maria Liakata,
Arkaitz Zubiaga, Rob Procter and Eric Jensen set out to find an effective approach for tack-
ling across-domain emotion classification task on a setof Twitter data involving social media
discourse around arts and cultural experiences, in the context of museums. Determining an
individual’s personality traits is an important concept in Psychology that is also synchronized
with our workshop’s themes. In this regard, Edward P. Tighe, Jennifer C. Ureta, Bernard
Andrei L. Pollo, Charibeth K. Cheng, and Remedios de Dios Bulos conducted research that
aims to perform feature reduction techniques on linguistic features from essays and classify the
author’s personality traits based on the reduced feature set.
Sandeep Sricharan Mukku, Nurendra Choudhary and Radhika Mamidi explored various
Machine Learning techniques for the classification of Telugu sentences into positive or negative
polarities. In the domain of Bio medical Natural Language Processing (Bio-NLP), Anupam
Mondal, Ranjan Satapathy, Dipankar Das and Sivaji Bandyopadhyay described a hybrid ap-
proach which is the combination of both linguistic and machine learning approaches to extract
the contextual sense-based information from a medical corpus.
Rafal Rzepka, Kohei Matsumoto and Kenji Araki introduced a novel method for utilizing
web mining and semantic categories for determining automatically if a given act is worth prais-
ing or not and reported how existing lexicons used in affective analysis and ethical judgment
can be combined for generating useful queries for knowledge retrieval from a 5.5 billion word
blog corpus. Finally, an approach to detect the sentiment of a song based on its multi-modality
natures (text and audio) is presented by Harika Abburi, Eswar Sai Akhil Akkireddy, Suryakanth
V Gangashetty and Radhika Mamidi.
We thank all the members of the Program Committee for their excellent and insightful
reviews, the authors who submitted contributions for the workshop and the participants for
making the workshop a success. We also express our thanks to the IJCAI 2016 Organizing
Committee and Local Organizing Committee for their support and cooperation in organizing
the workshop.
Organizing Committee
4thWorkshop on Sentiment Analysis where AI meets Psychology (SAAIP 2016)
IJCAI 2016
July 10, 2016
New York, USA
iii
SAAIP 2016
Organizing Committee
Sivaji Bandyopadhyay Jadavpur University, Kolkata (India) (Chair)
Dipankar Das Jadavpur University, Kolkata (India) (Co-Chair)
Erik Cambria Nanyang Technological University, Nanyang (Singapore)
Braja Gopal Patra Jadavpur University, Kolkata (India)
Program Committee
Alexandra Balahur European Commission Joint Research Centre (Italy)
Amitava Das IIIT Sri City (India)
Alexander Gelbukh Instituto Politécnico Nacional (Mexico)
Diana Inkpen University of Ottawa (Canada)
Vladimir Ivanov Kazan Federal University (Russia)
Saif Mohammad NRC (Canada)
Vincent Ng University of Texas at Dallas (USA)
Viviana Patti University of Turin (Italy)
Veronica Perez-Rosas University of Michigan (USA)
Paolo Rosso Technical University of Valencia (Spain)
Patrick Saint-Dizier IRIT-CNRS (France)
Yohei Seki University of Tsukuba (Japan)
Swapna Somasundaran Educational Testing Services (USA)
Veselin Stoyanov Johns Hopkins University (USA)
Stan Szpakowicz EECS, University of Ottawa (Canada)
Alessandro Valitutti University of Helsinki (Ireland)
Michael Zock CNRS-LIF (France)
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SAAIP 2016
Table of Contents
Invited Talk
7 Essential Principles to Make Multimodal Sentiment AnalysisWork in the Wild . . . . . . . . . . 1
Björn W. Schuller
Papers
WISE: Web-based Interactive Speech Emotion Classification. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2
Sefik Emre Eskimez, Melissa Sturge-Apple, Zhiyao Duan and Wendi Heinzelman
Exposing a Set of Fine-Grained Emotion Categories from Tweets . . . . . . . . . . . . . . . . . . . . . . . . . 8
Jasy Suet Yan Liew and Howard R. Turtle
SMILE: Twitter Emotion Classification using Domain Adaptation . . . . . . . . . . . . . . . . . . . . . . . . 15
Bo Wang, Maria Liakata, Arkaitz Zubiaga, Rob Procter and Eric Jensen
Personality Trait Classification of Essays with the Application of Feature Reduction . . . . . . 22
Edward P. Tighe, Jennifer C. Ureta, Bernard Andrei L. Pollo, Charibeth K. Cheng
and Remedios De Dios Bulos
Enhanced Sentiment Classification of Telugu Text using ML Techniques . . . . . . . . . . . . . . . . . . 29
Sandeep Sricharan Mukku, Nurendra Choudhary and Radhika Mamidi
Praiseworthy Acts Recognition Using Web-based Knowledge and Semantic Categories . . . . 35
Rafal Rzepka, Kohei Matsumoto and Kenji Araki
A Hybrid approach based Sentiment extraction from Medical context . . . . . . . . . . . . . . . . . . . . . 42
Anupam Mondal, Ranjan Satapathy, Dipankar Das and Sivaji Bandyopadhyay
Multimodal Sentiment Analysis of Telugu Songs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48
Harika Abburi, Eswar Sai Akhil Akkireddy, Suryakanth Gangashetti and Radhika
Mamidi
v
SAAIP 2016
Program Schedule
Session 1:
11:00 - 11:10 Opening Remarks
11:10 - 12:10 Invited Talk: 7 Essential Principles to Make Multimodal
Sentiment Analysis Work in the Wild
Björn W. Schuller
12:10 - 12:30 WISE: Web-based Interactive Speech Emotion Classification
Sefik Emre Eskimez, Melissa Sturge-Apple, Zhiyao Duan and
Wendi Heinzelman
12:30 - 14:00 Lunch
Session 2:
14:00 - 14:20 Exposing a Set of Fine-Grained Emotion Categories from
Tweets
Jasy Suet Yan Liew and Howard R. Turtle
14:20 - 14:40 SMILES: Twitter Emotion Classification using Domain
Bo Wang, Maria Liakata, Arkaitz Zubiaga, Rob Procter and
Eric Jensen
14:40 - 15:00 Personality Trait Classification of Essays with the Application
of Feature Reduction
Edward P. Tighe, Jennifer C. Ureta, Bernard Andrei L. Pollo,
Charibeth K. Cheng and Remedios De Dios Bulos
15:00 - 15:20 Enhanced Sentiment Classification of Telugu Text using ML
Techniques
Sandeep Sricharan Mukku, Nurendra Choudhary and Radhika
Mamidi
15:30 - 16:00 Coffee
vi
SAAIP 2016
Program Schedule
Session 3:
16:00 - 16:20 A Hybrid approach based Sentiment extraction from Medical
context
Anupam Mondal, Ranjan Satapathy, Dipankar Das and Sivaji
Bandyopadhyay
16:20 - 16:40 Praiseworthy Acts Recognition Using Web-based Knowledge
and Semantic Categories
Rafal Rzepka, Kohei Matsumoto and Kenji Araki
16:40 - 17:00 Multimodal Sentiment Analysis of Telugu Songs
Harika Abburi, Eswar Sai Akhil Akkireddy, Suryakanth Gan-
gashetti and Radhika Mamidi
17:00 - 17:30 Open Discussion and Valedictory
vii