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WISDOM 2012 : Workshop on Issues of Sentiment Discovery and Opinion Mining

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Link: http://sentic.net/wisdom
 
When Aug 12, 2012 - Aug 12, 2012
Where Beijing
Submission Deadline May 2, 2012
Notification Due Jun 2, 2012
Final Version Due Jun 12, 2012
Categories    opinion mining   sentiment analysis   NLP   social web
 

Call For Papers

WISDOM (Workshop on Issues of Sentiment Discovery and Opinion Mining) 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 ACM KDD 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.

ABSTRACT
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.

TOPICS
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 interdisciplinary challenges of opinion mining and sentiment analysis. 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

INVITED SPEAKER
Bing Liu is a professor of Computer Science at University of Illinois at Chicago (UIC). He received his PhD in Artificial Intelligence from the University of Edinburgh. Before joining UIC, he was with the National University of Singapore. His current research interests include opinion mining and sentiment analysis, Web mining, and data mining. He has published extensively in leading conferences and journals in these fields. He has also written a textbook titled “Web Data Mining: Exploring Hyperlinks, Contents and Usage Data” published by Springer. The second edition of the book came out in July 2011. On professional services, Liu has served as program chairs of ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), IEEE International Conference on Data Mining (ICDM), ACM Conference on Web Search and Data Mining (WSDM), SIAM Conference on Data Mining (SDM), ACM Conference on Information and Knowledge Management (CIKM), and Pacific Asia Conference on Data Mining (PAKDD). Additionally, he has also served as associate editors of IEEE Transactions on Knowledge and Data Engineering (TKDE), Journal of Data Mining and Knowledge Discovery (DMKD), and SIGKDD Explorations, and is on the editorial boards of several other journals.

TIMEFRAME
• May 2nd, 2012: Due date for workshop papers
• June 2nd, 2012, 2011: Notification of paper acceptance to authors
• June 12th, 2012, 2011: Camera-ready of accepted papers
• August 12th, 2012: Workshop date

PROGRAM COMMITTEE
• Alexandra Balahur, University of Alicante (Spain)
• Sandra Baldassarri, University of Zaragoza (Spain)
• Catherine Baudin, eBay Research Labs (USA)
• Eva Cerezo, University of Zaragoza (Spain)
• Praphul Chandra, HP Labs India (India)
• Amitava Das, Norwegian University of Science and Technology (Norway)
• Dipankar Das, Jadavpur University (India)
• Sergio Decherchi, Italian Institute of Technology (Italy)
• Rafael Del Hoyo, Aragon Institute of Technology (Spain)
• Tariq Durrani, University of Strathclyde (UK)
• Paolo Gastaldo, University of Genoa (Italy)
• Marco Grassi, Marche Polytechnic University (Italy)
• Minlie Huang, Tsinghua University (China)
• Isabelle Hupont, Aragon Institute of Technology (Spain)
• Amir Hussain, University of Stirling (UK)
• Raymond Lau, City University of Hong Kong (Hong Kong)
• Shixia Liu, Microsoft Research Asia (China)
• Saif Mohammad, National Research Council (Canada)
• Samaneh Moghaddam, Simon Fraser University (Canada)
• Muaz Niazi, Bahria University (Pakistan)
• Bjoern Schuller, Technical University of Munich (Germany)
• Stefano Squartini, Marche Polytechnic University (Italy)
• Kam-Fai Wong, Chinese University of Hong Kong (Hong Kong)
• Rui Xia, Nanjing University of Science and Technology (China)
• Lei Zhang, University of Illinois at Chicago (USA)

ORGANIZERS
• Erik Cambria, National University of Singapore (Singapore)
• Yongzheng Zhang, eBay Research Labs (USA)
• Yunqing Xia, Tsinghua University (China)
• Newton Howard, MIT Media Laboratory (USA)

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