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

被引:3
|
作者
Bele, Nishikant [1 ]
Panigrahi, Prabin Kumar [2 ]
Srivastava, Shashi Kant [3 ]
机构
[1] Int Inst Hlth Management Res, New Delhi, India
[2] Indian Inst Management Indore, Area Informat Syst, Indore, Madhya Pradesh, India
[3] Indian Inst Management Indore, Informat Syst, Indore, Madhya Pradesh, India
关键词
Blog Reviews; Feature Level Opinion Mining; Hindi Language; Information Search and Retrieval; Natural Languages Processing; Test Mining;
D O I
10.4018/IJKM.2018010101
中图分类号
C93 [管理学];
学科分类号
12 ; 1201 ; 1202 ; 120202 ;
摘要
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.
引用
收藏
页码:1 / 18
页数:18
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