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
References
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20 May 2003
TL;DR: This work develops a method for automatically distinguishing between positive and negative reviews and draws on information retrieval techniques for feature extraction and scoring, and the results for various metrics and heuristics vary depending on the testing situation.
Abstract: The web contains a wealth of product reviews, but sifting through them is a daunting task. Ideally, an opinion mining tool would process a set of search results for a given item, generating a list of product attributes (quality, features, etc.) and aggregating opinions about each of them (poor, mixed, good). We begin by identifying the unique properties of this problem and develop a method for automatically distinguishing between positive and negative reviews. Our classifier draws on information retrieval techniques for feature extraction and scoring, and the results for various metrics and heuristics vary depending on the testing situation. The best methods work as well as or better than traditional machine learning. When operating on individual sentences collected from web searches, performance is limited due to noise and ambiguity. But in the context of a complete web-based tool and aided by a simple method for grouping sentences into attributes, the results are qualitatively quite useful.
2,238 citations
TL;DR: This article introduces a method for inferring the semantic orientation of a word from its statistical association with a set of positive and negative paradigm words, based on two different statistical measures of word association.
Abstract: The evaluative character of a word is called its semantic orientation. Positive semantic orientation indicates praise (e.g., "honest", "intrepid") and negative semantic orientation indicates criticism (e.g., "disturbing", "superfluous"). Semantic orientation varies in both direction (positive or negative) and degree (mild to strong). An automated system for measuring semantic orientation would have application in text classification, text filtering, tracking opinions in online discussions, analysis of survey responses, and automated chat systems (chatbots). This article introduces a method for inferring the semantic orientation of a word from its statistical association with a set of positive and negative paradigm words. Two instances of this approach are evaluated, based on two different statistical measures of word association: pointwise mutual information (PMI) and latent semantic analysis (LSA). The method is experimentally tested with 3,596 words (including adjectives, adverbs, nouns, and verbs) that have been manually labeled positive (1,614 words) and negative (1,982 words). The method attains an accuracy of 82.8p on the full test set, but the accuracy rises above 95p when the algorithm is allowed to abstain from classifying mild words.
1,651 citations
31 May 2009
TL;DR: This paper presents and compares WordNet-based and distributional similarity approaches, and pioneer cross-lingual similarity, showing that the methods are easily adapted for a cross-lingsual task with minor losses.
Abstract: This paper presents and compares WordNet-based and distributional similarity approaches. The strengths and weaknesses of each approach regarding similarity and relatedness tasks are discussed, and a combination is presented. Each of our methods independently provide the best results in their class on the RG and WordSim353 datasets, and a supervised combination of them yields the best published results on all datasets. Finally, we pioneer cross-lingual similarity, showing that our methods are easily adapted for a cross-lingual task with minor losses.
936 citations
TL;DR: Alesina et al. as mentioned in this paper showed that the degree of politico-institutional stability and the independence of the Central Bank have a bearing on macroeconomic outcomes. But they also pointed out that the combination of partisanship and electoral cycles may easily result in socially undesirable outcomes.
Abstract: Politics
Alberto Alesina
Influences from political competition on macroeconomic policy are often thought to be a source of economic fluctuations. Politicians are described as being driven by two, not mutually exclusive, main motivations: they want to be reelected and they harbour political, or ideological, biases. When such theories are confronted with actual cycles in a number of industrial countries, the pattern of inflation, unemployment, output, and budget deficits indicates that partisan policy making is a fairly widespread phenomenon, with more limited evidence that electoral preoccupations result in major fluctuations. The combination of partisanship and electoral cycles may easily result in socially undesirable outcomes. In particular the degree of politico-institutional stability and the independence of the Central Bank have a bearing on macroeconomic outcomes. These observations raise a number of important questions about the design of political institutions.
485 citations
TL;DR: In this paper, the authors developed and tested a simple mod-el for the use of political strategies, such as lobbying the government for trade protection, in the strategic management literature.
Abstract: An underplayed topic in the strategic management literature is firms' use of political strategies, such as lobbying the government for trade protection. This study developed and tested a simple mod...
338 citations
Additional excerpts
...Businessgrowthisdependenton 55 International Journal of Business Intelligence Research Volume 8 • Issue 1 • January-June 2017 56 thepoliticalenvironment(Schuler,1996;Shaffer&Hillman,2000)....
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