KDD 2012 Workshop

Workshop on Issues of Sentiment Discovery and Opinion Mining (WISDOM’13)

Overview

The exponential growth of the Social Web is virally infecting more and more critical business processes such as customer support and satisfaction, brand and reputation management, product design and marketing. Because of this global trend, web users already evolved from the era of social relationships, in which they began to get connected and started to share contents, to the era of social functionality, in which they started using social networks as the main platform for communication and dissemination of information. Today, web users are going through the era of social colonization, in which every experience on the Web can be social (e.g., Facebook Like button), and are getting ready for the era of social context, in which web contents will be highly targeted and personalized. The final stage of such Social Web evolution is the so called era of social commerce, in which communities will define future products and services. In such context, the research field of sentiment analysis, which has already been rapidly growing in the last decade, is destined to become more and more important for Web and business dynamics. To this end, the Second International Workshop on Issues of Sentiment Discovery and Opinion Mining (WISDOM 2013: http://sentic.net/wisdom/) aims to explore how the wisdom of the crowds is affecting (and will affect) the evolution of the Web and of businesses gravitating around it. In particular, the workshop explores two different stages of sentiment analysis: the former focusing on the identification of opinionated text over the Web, the latter focusing on the classification of such text either in terms of polarity detection or emotion recognition.

Topics of Interest

The workshop will provide an international forum for both researchers and entrepreneurs working in the field of opinion mining to share information on their latest investigations in social information retrieval and their applications in academic research areas and industrial sectors. The broader context of the workshop comprehends AI, Semantic Web, information retrieval, web mining, and natural language processing (NLP). In addition to paper presentations, an invited talk by Professor Bing Liu will stress the problem of detecting fake opinions in social media. Topics of interest include but are not limited to:

· Sentiment identification & classification

· Knowledge-based opinion mining

· Sentiment summarization & visualization

· Entity discovery & extraction

· Opinion aggregation

· Opinion search & retrieval

· Time evolving sentiment analysis

· Opinion spam detection

· Comparative opinion analysis

· Topic detection & trend discovery

· Psychological models for sentiment analysis

· Multilingual opinion mining

· Social ranking

· Social network analysis

· Influence, trust & privacy analysis

· Business intelligence applications

Schedule Return to Top

Workshop Schedule at a Glance
August 11, 2013 Sunday
09:00-10:10	Opening Remarks
09:00-10:10	· Keynote Speech: Statistical Methods for Integration and Analysis of Opinionated Text Data Chengxiang Zhai, University of Illinois at Urbana-Champaign
10:10-10:30	Morning Break
10:30-12:00	Session 1 · Identifying Purpose Behind Electoral Tweets Saif M. Mohammad, Svetlana Kiritchenko, and Joel Martin · Combining Strengths, Emotions and Polarities for Boosting Twitter Sentiment Analysis Felipe Bravo-Marquez, Marcelo Mendoza, and Barbara Poblete · Modelling Political Disaffection from Twitter Data Corrado Monti, Alessandro Rozza, Giovanni Zappella, Matteo Zignani, Adam Arvidsson, and Elanor Colleoni
12:00-13:30	Lunch Break
13:30-15:30	Session 2 · Enhancing Sentiment Extraction from Text by Means of Arguments Lucas Carstens and Francesca Toni · Evaluation of an Algorithm for Aspect-Based Opinion Mining Using a Lexicon-Based Approach Florian Wogenstein, Johannes Drescher, Dirk Reinel, Sven Rill, and Jörg Scheidt · Commonsense-Based Topic Modeling Dheeraj Rajagopal, Daniel Olsher, Erik Cambria, and Kenneth Kwok · Online Debate Summarization using Topic Directed Sentiment Analysis Sarvesh Ranade, Jayant Gupta, Vasudeva Varma, and Radhika Mamidi
15:30-16:00	Afternoon Break
16:00-17:30	Session 3 · RBEM: A Rule Based Approach to Polarity Detection Erik Tromp and Mykola Pechenizkiy · Cross-lingual Polarity Detection with Machine Translation Erkin Demirtas and Mykola Pechenizkiy · Sentribute: Image Sentiment Analysis from a Mid-level Perspective Jianbo Yuan, Quanzeng You, Sean Mcdonough, and Jiebo Luo
16:00-17:30	Closing Remarks

Invited Speaker Return to Top

Chengxiang Zhai, University of Illinois at Urbana-Champaign (USA)

Title: Statistical Methods for Integration and Analysis of Opinionated Text Data

Abstract: Opinionated text data such as blogs, forum posts, product reviews and online comments are increasingly available on the Web. They are very useful sources for public opinions about virtually any topics. However, because the opinions are scattered and abundant, it is a significant challenge for users to collect all the opinions about a topic and digest them efficiently. In this talk, I will present a suite of general statistical text mining methods that can help users integrate, summarize and analyze scattered online opinions to obtain actionable knowledge for decision making. Specifically, I will first present approaches to integration of scattered opinions by aligning them to a well-structured article or relevant ontology. Second, I will discuss several techniques for generating a concise opinion summary that can reveal the major sentiments and opinion points buried in large amounts of opinionated text data. Finally, I will present probabilistic general models for analyzing review data in depth to discover latent aspect ratings and relative weights placed by reviewers on different aspects. These methods are completely general and can thus help users integrate and analyze large amounts of online opinionated text data on any topic in any natural language.

Bio: Chengxiang Zhai is an Associate Professor of Computer Science at the University of Illinois at Urbana-Champaign, where he is also affiliated with the Graduate School of Library and Information Science, Institute for Genomic Biology, and Department of Statistics. He received a Ph.D. in Computer Science from Nanjing University in 1990, and a Ph.D. in Language and Information Technologies from Carnegie Mellon University in 2002. He worked at Clairvoyance Corp. as a Research Scientist and a Senior Research Scientist from 1997 to 2000. His research interests include information retrieval, text mining, natural language processing, machine learning, and biomedical informatics, in which he published over 150 research papers. He is an Associate Editor of ACM Transactions on Information Systems, and Information Processing and Management, and serves on the editorial board of Information Retrieval Journal. He is a program co-chair of ACM CIKM 2004, NAACL HLT 2007, and ACM SIGIR 2009. He is an ACM Distinguished Scientist and a recipient of multiple best paper awards, Alfred P. Sloan Research Fellowship, IBM Faculty Award, HP Innovation Research Program Award, and the Presidential Early Career Award for Scientists and Engineers (PECASE).

Table of Contents Return to Top

Full Papers

Identifying Purpose Behind Electoral Tweets
Saif M. Mohammad, Svetlana Kiritchenko, and Joel Martin

Combining Strengths, Emotions and Polarities for Boosting Twitter Sentiment Analysis
Felipe Bravo-Marquez, Marcelo Mendoza, and Barbara Poblete

Modelling Political Disaffection from Twitter Data
Corrado Monti, Alessandro Rozza, Giovanni Zappella, Matteo Zignani, Adam Arvidsson, and Elanor Colleoni

Enhancing Sentiment Extraction from Text by Means of Arguments
Lucas Carstens and Francesca Toni

Evaluation of an Algorithm for Aspect-Based Opinion Mining Using a Lexicon-Based Approach
Florian Wogenstein, Johannes Drescher, Dirk Reinel, Sven Rill, and Jörg Scheidt

Commonsense-Based Topic Modeling
Dheeraj Rajagopal, Daniel Olsher, Erik Cambria, and Kenneth Kwok

Online Debate Summarization using Topic Directed Sentiment Analysis
Sarvesh Ranade, Jayant Gupta, Vasudeva Varma, and Radhika Mamidi

RBEM: A Rule Based Approach to Polarity Detection
Erik Tromp and Mykola Pechenizkiy

Cross-lingual Polarity Detection with Machine Translation
Erkin Demirtas and Mykola Pechenizkiy

Sentribute: Image Sentiment Analysis from a Mid-level Perspective
Jianbo Yuan, Quanzeng You, Sean Mcdonough, and Jiebo Luo

Organizers Return to Top

Organizing Committee

· Erik Cambria, National University of Singapore (Singapore)

· Bing Liu, University of Illinois at Chicago (USA)

· Yongzheng Zhang, eBay Inc. (USA)

· Yunqing Xia, Tsinghua University (China)

Program Committee

· Hisham Al-Mubaid, University of Houston at Clear Lake (USA)

· Alexandra Balahur, European Commission Joint Research Center (Italy)

· Cristina Bosco, Università di Torino (Italy)

· Ping Chen, University of Houston – Downtown (USA)

· Rossana Damiano, Università di Torino (Italy)

· Amitava Das, Norwegian University of Science and Technology (Norway)

· Dipankar Das, Jadavpur University (India)

· Giuseppe Di Fabbrizio, Amazon Inc. (USA)

· Viswanath Gopalakrishnan, Samsung Research India (India)

· Marco Grassi, Marche Polytechnic University (Italy)

· Rafael del Hoyo, Aragon Institute of Technology (Spain)

· Saif Mohammad, National Research Council (Canada)

· Muaz Niazi, Bahria University (Pakistan)

· Viviana Patti, Università di Torino (Italy)

· Rui Xia, Nanjing University of Science and Technology (China)

· Yunqing Xia, Tsinghua University (China)

· Yusheng Xie, Northwestern University (USA)

· Chengxiang Zhai, University of Illinois at Urbana-Champaign (USA)

· Lei Zhang, University of Illinois at Chicago (USA)

· Yongzheng Zhang, eBay Inc. (USA)

Sponsors Return to Top