Political Sentiment Mining: A New Age Intelligence Tool for Business Strategy Formulation
01 Jan 2017-International Journal of Business Intelligence Research (IGI Global)-Vol. 8, Iss: 1, pp 55-70
TL;DR: Investigating Document Level Opinion Mining, Hindi Blogs Reviews, Hindi Language, Information Search and Retrieval, Machine Learning Techniques, Natural Languages Processing, Opinion Mining.
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 langua...
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18 Feb 2022
TL;DR: In this article , the authors conducted a systematic literature review based on PRISMA methodology to identify the most frequently used lexicons in political sentiment analysis, their results, similarities, and differences.
Abstract: This chapter presented an analysis of the application of lexicon-based political sentiment analysis in social media. The aim is to identify the most frequently used lexicons in political sentiment analysis, their results, similarities, and differences. For this, the authors conducted a systematic literature review based on PRISMA methodology. Afinn, NRC, and SenticNet lexicons are tested and combined for data analysis from the 2020 U.S. presidential campaign. Findings show that political sentiment analysis is a new field studied for only 10 years. Political sentiment analysis could generate benefits in understanding problems such as political polarization, discourse analysis, politician influence, candidate profiling, and improving government-citizen interaction, among other problems in the public sphere, enhanced by the combination of lexicons and multimodal analysis. The authors conclude that polarity was one of the critical dimensions identified for finding variations in the behavior and polarity of sentiments. Limitations and future work also are presented.
4 citations
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TL;DR: In this article, it has been used hundreds of years ago to turn waterwheels for different purposes such as grind-ing grains, sawing logs, and sawing log logs.
Abstract: Hydro power is one of the oldest sources of energy used by human civilization. It has been used hundreds of years ago to turn waterwheels for different purposes such as grind-ing grains, sawing log ...
251 citations
247 citations
18 Apr 2009
TL;DR: The experimental results indicate that proposed approach could improve the performance of base classifier dramatically, and even provide much better performance than the transfer-learning baseline, i.e. the Naive Bayes Transfer Classifier (NTBC).
Abstract: In the community of sentiment analysis, supervised learning techniques have been shown to perform very well. When transferred to another domain, however, a supervised sentiment classifier often performs extremely bad. This is so-called domain-transfer problem. In this work, we attempt to attack this problem by making the maximum use of both the old-domain data and the unlabeled new-domain data. To leverage knowledge from the old-domain data, we proposed an effective measure, i.e., Frequently Co-occurring Entropy (FCE), to pick out generalizable features that occur frequently in both domains and have similar occurring probability. To gain knowledge from the new-domain data, we proposed Adapted Naive Bayes (ANB), a weighted transfer version of Naive Bayes Classifier. The experimental results indicate that proposed approach could improve the performance of base classifier dramatically, and even provide much better performance than the transfer-learning baseline, i.e. the Naive Bayes Transfer Classifier (NTBC).
210 citations
TL;DR: In this paper, the authors explore internal conflicts in the formulation of business-government strategies by corporations with diversified business units and find that three types of conflict exist within firms: conflict over proactive policy positions advocated by the firm, conflict over reactive internal distribution of compliance costs/benefits, and representational conflict.
Abstract: This paper uses grounded theory to explore internal (intrafirm) conflicts in the formulation of business–government strategies by corporations with diversified business units. We find that three types of conflict exist within firms: conflict over proactive policy positions advocated by the firm (prepolicy issues), conflict over reactive internal distribution of compliance costs/benefits (postpolicy issues), and representational conflict (e.g., individual business units vs. corporate representation in the external public policy arena). We also develop a grounded framework for organizational structures for conflict resolution in the strategic management of government relations, based upon our case studies, and find a relationship between particular structures and the degree of diversification. Copyright © 2000 John Wiley & Sons, Ltd.
200 citations
01 Jan 2010
TL;DR: This paper proposes in this paper a fall-back strategy to do sentiment analysis for Hindi documents, a problem on which, to the best of the knowledge, no work has been done until now.
Abstract: Sentiment Analysis (SA) research has gained tremendous momentum in recent times. However, there has been little work in this area for an Indian language. We propose in this paper a fall-back strategy to do sentiment analysis for Hindi documents, a problem on which, to the best of our knowledge, no work has been done until now. (A) First of all, we study three approaches to perform SA in Hindi. We have developed a sentiment annotated corpora in the Hindi movie review domain. The first of our approaches involves training a classifier on this annotated Hindi corpus and using it to classify a new Hindi document. (B) In the second approach, we translate the given document into English and use a classifier trained on standard English movie reviews to classify the document. (C) In the third approach, we develop a lexical resource called Hindi-SentiWordNet (H-SWN) and implement a majority score based strategy to classify the given document.
147 citations