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Join us for a tutorial on Applications of Social Media Text Analysis presented by Dr. Farzindar, CEO of NLP, at EMNLP 2015, September 18, Lisbon, Portugal




We proudly invite you to attend a tutorial organized by one of the most prestigious conferences in the computational linguistics community, EMNLP (Empirical Methods in Natural Language Processing). The 2015 EMNLP Conference will be held September 17–21, 2015 in Lisbon, Portugal.
The tutorial focuses on innovative applications of Social Media Text Analysis, and will be presented by Dr. Atefeh Farzindar, CEO of NLP Technologies and Dr. Diana Inkpen, from the University of Ottawa. For more information on EMNLP and registration, please visit http://emnlp2015.emnlp.org/
 

Applications of Social Media Text Analysis

Atefeh Farzindar and Diana Inkpen
 
September 18, 2015 – Morning

Abstract:

Analyzing social media texts is a complex problem that becomes difficult to address using traditional Natural Language Processing (NLP) methods. Our tutorial focuses on presenting new methods for NLP tasks and applications that work on noisy and informal texts, such as the ones from social media. Automatic processing of large collections of social media texts is important because they contain a lot of useful information, due to the in-creasing popularity of all types of social media. Use of social media and messaging apps grew 203 percent year-on-year in 2013, with overall app use rising 115 percent over the same period, as reported by Statista, citing data from Flurry Analytics. This growth means that 1.61 billion people are now active in social media around the world and this is expected to advance to 2 billion users in 2016, led by India. The research shows that consumers are now spending daily 5.6 hours on digital media including social media and mo-bile internet usage.

At the heart of this interest is the ability for users to create and share content via a variety of platforms such as blogs, micro-blogs, collaborative wikis, multimedia sharing sites, social net-working sites. The unprecedented volume and variety of user-generated content, as well as the user interaction network constitute new opportunities for understanding social behavior and building socially intelligent systems. Therefore it is important to investigate methods for knowledge extraction from social media data. Furthermore, we can use this information to detect and retrieve more related content about events, such as photos and video clips that have caption texts.

Instructors:

Atefeh Farzindar, Adjunct Professor, University of Montreal

Dr. Atefeh Farzindar is the CEO of NLP Technologies Inc. and Adjunct Professor at University of Montreal. She has served as Chair of the technology sector of the Language Industry Association Canada (AILIA) (2009-2013), Vice-president of The Language Technologies Research Centre (LTRC) of Canada (2012-2014) and a member of the Natural Sciences and Engineering Research Council of Canada (NSERC) Computer Science Liaison Committee (2014-2015). Recently, she authored a book chapter in Social Network Integration in Document Summarization, Innovative Document Summarization Techniques: Revolutionizing Knowledge Understanding, IGI Global publisher January 2014.

Diana Inkpen, Professor, University of Ottawa

Dr. Diana Inkpen is a Professor at the School of Electrical Engineering and Computer Science at the University of Ottawa. 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, extraction of semantic frames, and lexical choice in natural language generation. She published more than 25 journal papers, 85 conference papers, and 6 book chapters. She is an associated editor of the Computational Intelligence and Natural Language Engineering journals.