Political Sentiment Mining

Author:

Bele Nishikant1,Panigrahi Prabin Kumar2,Srivastava Shashi Kant2

Affiliation:

1. International Institute of Health Management Research (IIHMR), New Delhi, India

2. Department of Information Systems, Indian Institute of Management Indore, Indore, India

Abstract

Investigations on sentiment mining are mostly ensued in the English language. Due to the characteristics of the Indian languages tools and techniques used for sentiment mining in the English language cannot be applied directly to text in Hindi languages. The objective of this paper is to extract the political sentiment at the document-level from Hindi blogs. The authors could not find any literature about extracting sentiments at the document-level from Hindi blogs. They extracted opinion about one of India's very famous leaders who was a prominent face in the national election of 2014. They prepared the datasets from Hindi blogs reviews. They purposed the lexicon and machine learning technique to classify the sentiment. Their purposed method used four steps: (1) Crawling and preprocessing the blog reviews; (2) Extracting reviews relevant to the query using the Vector Space Model (VSM); (3) Identifying sentiment at the document level using the Lexicon method, and (4) Measuring the result using the Machine learning technique. Their experimental result demonstrates the effectiveness of our algorithms.

Publisher

IGI Global

Subject

Information Systems and Management,Statistics, Probability and Uncertainty,Management Information Systems

Reference49 articles.

1. Politics and Business Cycles in Industrial Democracies

2. Data Mining Approach to Decision Support in Social Welfare

3. Closing the Gap between Data Mining and Business Users of Business Intelligence Systems

4. Bakliwal, A., Arora, P., & Varma, V. (2012). Hindi Subjective Lexicon: A Lexical Resource for Hindi Polarity Classification. In The eighth international conference on Language. Resources and Evaluation. Retrieved from http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.475.3838&rep=rep1&type=pdf

5. Indirect Learning: How Emerging-Market Firms Grow in Developed Markets

Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Features level sentiment mining in enterprise systems from informal text corpus using machine learning techniques;Enterprise Information Systems;2024-03-24

2. Review on the Application of Lexicon-Based Political Sentiment Analysis in Social Media;Handbook of Research on Opinion Mining and Text Analytics on Literary Works and Social Media;2022-02-18

3. Multi-agent simulation modeling of online Internet discussions;Business Informatics;2018-06-30

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3