Political Sentiment Mining: A New Age Intelligence Tool for Business Strategy Formulation

Nishikant Bele, Prabin Kumar Panigrahi and Shashi Kant Srivastava
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Nishikant Bele: International Institute of Health Management Research (IIHMR), 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 Business Intelligence Research (IJBIR), 2017, vol. 8, issue 1, 55-70

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.

Date: 2017
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