Natural Language Processing for Social Media
Natural Language Processing for Social Media
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This book presents the state-of-the-art in research and empirical studies in the field of Natural Language Processing (NLP) for the semantic analysis of social media data. Over the past few years, online social networking sites have revolutionized the way we communicate with individuals, groups and communities, and altered everyday practices. The unprecedented volume and variety of user-generated content and the user interaction network constitute new opportunities for understanding social behavior and building socially intelligent systems
Much research work on social networks and the mining of the social web is based on graph theory. That is apt because a social structure is made up of a set of social actors and a set of the dyadic ties between these actors. We believe that the graph-mining methods for structure, information diffusion or influence spread in social networks needs to combined with the content analysis of social media. This provides the opportunity for new applications that use the information publicly available as a result of social interactions.
The intended audience of this book is researchers who are interested in developing tools and applications for automatic analysis of social media texts. We assume that the readers have basic knowledge in the area of natural language processing and machine learning. This book will help the readers better understand computational linguistics and social media analysis, in particular text-mining techniques and NLP applications (such as summarization, localization detection, sentiment and emotion analysis, topic detection and machine translation) designed specifically for social media texts.
Table of Contents
Introduction to Social Media Analysis
Linguistic Pre-processing of Social Media Texts
Semantic Analysis of Social Media Texts
Applications of Social Media Text Analysis
Data Collection, Annotation, and Evaluation
Conclusion and Perspectives
About the Author(s)
Atefeh Farzindar, NLP Technologies, Inc.
Dr. Atefeh Farzindar is the CEO and co-founder of NLP Technologies, which was founded in Montreal, Quebec, in 2005, and expanded to California in 2014. The company specializes in natural language processing, knowledge engineering, NLP-based search engines, machine translation, social media analytics, and automatic summarization. She received her Ph.D. in Computer Science from the UniversitÃ© de MontrÃ©al and her Doctorate from Paris-Sorbonne University on automatic summarization of legal documents in 2005. She is an adjunct professor in the Department of Computer Science at the University of Montreal, and the chair of the language technologies sector of the Canadian Language Industry Association (AILIA). Dr. Farzindar has been serving as a member of the Natural Sciences and Engineering Research Council of Canada (NSERC), the Computer Science Liaison Committee, and the Canadian Advisory Committee to International Organization for Standardization (ISO) since 2011. She is vice president and an executive member of the Board of Directors of The Language Technologies Research Centre (LTRC) of Canada. Dr. Farzindar was the General Chair of the 2014 AI/GI/CRV Conference, the most important Canadian conference in computer science, which is a collaboration of three leading conferences: Artificial Intelligence, Graphics Interface, and Computer and Robot Vision. She published more than 35 papers, authored three books and recently a chapter in a book on Social Network Integration in Document Summarization, published by IGI Global, and titled Innovative Document Summarization Techniques: Revolutionizing Knowledge Understanding.
Diana Inkpen, University of Ottawa
Dr. Diana Inkpen is a Professor at the School of Electrical Engineering and Computer Science at the University of Ottawa, ON, Canada. She obtained her Ph.D. in 2003 from the University of Toronto, Department of Computer Science. She obtained her M.Sc. from the Department of Computer Science, Technical University of Cluj-Napoca, Romania, in 1995, and a B.Eng. from the same university, in 1994. Her research interests and expertise are in natural language processing, in particular lexical semantics as applied to near synonyms and nuances of meaning, word and text similarity, classification of texts by emotion and mood, information retrieval from spontaneous speech, information extraction, and lexical choice in natural language generation. Dr. Inkpen was Program Committee co-chair for the twenty-fifth Canadian Conference on Artificial Intelligence (AI 2012), Toronto, Canada, May 2012, for the 7th IEEE International Conference on Natural Language Processing and Knowledge Engineering (IEEE NLP-KE’11), Tokushima, Japan, November 2011 and for the 6th IEEE International Conference on Natural Language Processing and Knowledge Engineering (IEEE NLP-KE’10), Beijing, China, August 2010. She was named Visiting Professor of Computational Linguistics at the University of Wolverhampton, UK, from September 2010 to August 2013. She led and continues to lead many research projects with funding from Natural Sciences and Engineering Research Council of Canada (NSERC), Social Sciences and Humanities Research Council of Canada (SSHRC), and Ontario Centres of Excellence (OCE). The projects include industrial collaborations with companies from Ottawa, Toronto, and Montreal. She published more than 25 journal papers, 90 conference papers, and eight book chapters. She was on the program committees of many conferences in her field, a reviewer for many journals, and an associate editor of the Computational Intelligence journal and the Natural Language Engineering journal.