Analysis of Online Social Networks for the Identification of Sarcasm

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Author(s): Pulkit Mehndiratta (Jaypee Institute of Information Technology, India)
Copyright: 2018
Pages: 14
Source title: Social Network Analytics for Contemporary Business Organizations
Source Author(s)/Editor(s): Himani Bansal (Jaypee Institute of Information Technology, India), Gulshan Shrivastava (National Institute of Technology Patna, India), Gia Nhu Nguyen (Duy Tan University, Vietnam)and Loredana-Mihaela Stanciu (University Timisoara, Romania)
DOI: 10.4018/978-1-5225-5097-6.ch006

Keywords: Business Information Systems / Business Science Reference / Media & Communications / Social Networking

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Abstract

With the ever-increasing acceptance of online social networks (OSNs), a new dimension has evolved for communication amongst humans. OSNs have given us the opportunity to monitor and mine the opinions of a large number of online active populations in real time. Many diverse approaches have been proposed, various datasets have been generated, but there is a need of collective understanding of this area. Researchers are working around the globe to find a pattern to judge the mood of the user; the still serious problem of detection of irony and sarcasm in textual data poses a threat to the accuracy of the techniques evolved till date. This chapter aims to help the reader to think and learn more clearly about the aspects of sentiment analysis, social network analysis, and detection of irony or sarcasm in textual data generated via online social networks. It argues and discusses various techniques and solutions available in literature currently. In the end, the chapter provides some answers to the open-ended question and future research directions related to the analysis of textual data.

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Analysis of Online Social Networks for the Identification of Sarcasm

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