LINGUIST List 29.3

Tue Jan 02 2018

Books: Natural Language Processing for Social Media: Farzindar, Inkpen

Editor for this issue: Michael Czerniakowski <mikelinguistlist.org>


Date: 20-Dec-2017
From: Bebe Barrow <barrowmorganclaypool.com>
Subject: Natural Language Processing for Social Media: Farzindar, Inkpen
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Title: Natural Language Processing for Social Media
Subtitle: Second Edition
Series Title: Synthesis Lectures on Human Language Technologies edited by Graeme Hirst
Published: 2017
Publisher: Morgan & Claypool Publishers
                http://www.morganclaypool.com

Book URL: http://www.morganclaypoolpublishers.com/catalog_Orig/product_info.php?products_id=1148

Author: Atefeh Farzindar
Author: Diana Inkpen
Electronic: ISBN: 9781681736136 Pages: 195 Price: U.S. $ 63.96
Hardback: ISBN: 9781681736143 Pages: 195 Price: U.S. $ 99.95
Paperback: ISBN: 9781681736129 Pages: 195 Price: U.S. $ 79.95
Abstract:

Editor's Note: This is a new edition of a previously announced 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 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, healthcare, business intelligence, industry, marketing, and security and defence.

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, virtual reality, and social networking.

In this second edition, we have added information about recent progress in the tasks and applications presented in the first edition. We discuss new methods and their results. The number of research projects and publications that use social media data is constantly increasing due to continuously growing amounts of social media data and the need to automatically process them. We have added 85 new references to the more than 300 references from the first edition. Besides updating each section, we have added a new application (digital marketing) to the section on media monitoring and we have augmented the section on healthcare applications with an extended discussion of recent research on detecting signs of mental illness from social media.

Linguistic Field(s): Computational Linguistics
                            Discourse Analysis
                            Semantics

Written In: English (eng)

See this book announcement on our website:
http://linguistlist.org/pubs/books/get-book.cfm?BookID=123193


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