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

Tue Jan 2 19:39:43 UTC 2018

LINGUIST List: Vol-29-3. Tue Jan 02 2018. ISSN: 1069 - 4875.

Subject: 29.3, Books: Natural Language Processing for Social Media: Farzindar, Inkpen

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Date: Tue, 02 Jan 2018 14:39:36
From: Bebe Barrow [barrow at morganclaypool.com]
Subject: Natural Language Processing for Social Media: Farzindar, Inkpen

Title: Natural Language Processing for Social Media 
Subtitle: Second Edition 
Series Title: Synthesis Lectures on Human Language Technologies edited by Graeme Hirst  

Publication Year: 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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