Knowledge Discovery From Vernacular Expressions: An Application of Social Media and Sentiment Mining

Nishikant Bele, Prabin Kumar Panigrahi and Shashi Kant Srivastava
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Nishikant Bele: International Institute of Health Management Research, New Delhi, India
Prabin Kumar Panigrahi: Department of Information Systems, Indian Institute of Management Indore, Indore, India
Shashi Kant Srivastava: Department of Information Systems, Indian Institute of Management Indore, Indore, India

International Journal of Knowledge Management (IJKM), 2018, vol. 14, issue 1, 1-18

Abstract: This article describes how knowledge discovery is a frontier research issue of knowledge management, and social media provides an opportunity for knowledge discovery that was at no other time as virtuous as the present. Despite the fact that, the articulations in national dialects via web-based networking media is mounting day by day. This discovery endeavor in regional languages is rare. The usage of Hindi, the Indian National language, is also observing the similar trend. Any expression in social media contains multiple features. Discovering the hidden sentiments behind these features have wider functions. This article is the first attempt to mine the opinion at the features level in the Hindi language. The principle contribution of this article is the development of context specific corpus in the Hindi language. Based on this corpus authors extract the sentiments on one of the prominent leader of India at the feature level. Opinion mining conclusion based on present work is reproduced likewise in the subsequent election results.

Date: 2018
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Persistent link: https://EconPapers.repec.org/RePEc:igg:jkm000:v:14:y:2018:i:1:p:1-18

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