About the Book
In recent years, online social networking has revolutionized interpersonal communication. The newer research on language analysis in social media has been increasingly focusing on the latter's impact on our daily lives, both on a personal and a professional level. Natural language processing (NLP) is one of the most promising avenues for social media data processing. It is a scientific challenge to develop powerful methods and algorithms which extract relevant information from a large volume of data coming from multiple sources and languages in various formats or in free form. We discuss the challenges in analyzing social media texts in contrast with traditional documents. Research methods in information extraction, automatic categorization and clustering, automatic summarization and indexing, and statistical machine translation need to be adapted to a new kind of data. This book reviews the current research on Natural Language Processing (NLP) tools and methods for processing the non-traditional information from social media data that is available in large amounts (big data), and shows how innovative NLP approaches can integrate appropriate linguistic information in various fields such as social media monitoring, health care, business intelligence, industry, marketing, and security and defense. We review the existing evaluation metrics for NLP and social media applications, and the new efforts in evaluation campaigns or shared tasks on new datasets collected from social media. Such tasks are organized by the Association for Computational Linguistics (such as SemEval tasks) or by the National Institute of Standards and Technology via the Text REtrieval Conference (TREC) and the Text Analysis Conference (TAC). In the concluding chapter, we discuss the importance of this dynamic discipline and its great potential for NLP in the coming decade, in the context of changes in mobile technology, cloud computing, and social networking.
About the Author :
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 Universite de Montreal 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 Universite de 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.
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.
