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A societal sentiment analysis: Predicting the values and ethics of individuals by analysing social media content
Indian Institute of Information Technology, India.
Indian Institute of Information Technology, India.
Indian Institute of Technology, India.
National Institute of Technology, India.
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2017 (English)In: 15th Conference of the European Chapter of the Association for Computational Linguistics, EACL 2017 - Proceedings of Conference, 2017, 731-741 p.Conference paper, Published paper (Refereed)
Abstract [en]

To find out how users' social media behaviour and language are related to their ethical practices, the paper investigates applying Schwartz' psycholinguistic model of societal sentiment to social media text. The analysis is based on corpora collected from user essays as well as social media (Facebook and Twitter). Several experiments were carried out on the corpora to classify the ethical values of users, incorporating Linguistic Inquiry Word Count analysis, n-grams, topic models, psycholinguistic lexica, speech-acts, and nonlinguistic information, while applying a range of machine learners (Support Vector Machines, Logistic Regression, and Random Forests) to identify the best linguistic and non-linguistic features for automatic classification of values and ethics.

Place, publisher, year, edition, pages
2017. 731-741 p.
Keyword [en]
Classification (of information), Computational linguistics, Decision trees, Linguistics, Philosophical aspects, Automatic classification, Ethical practices, Ethical values, Linguistic features, Logistic regressions, Machine learners, Psycholinguistic models, Sentiment analysis, Social networking (online)
National Category
Computer and Information Science
Identifiers
URN: urn:nbn:se:ri:diva-31136Scopus ID: 2-s2.0-85021625321ISBN: 9781510838604 OAI: oai:DiVA.org:ri-31136DiVA: diva2:1136476
Conference
15th Conference of the European Chapter of the Association for Computational Linguistics, EACL 2017, 3 April 2017 through 7 April 2017
Available from: 2017-08-28 Created: 2017-08-28 Last updated: 2017-08-29Bibliographically approved

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  • en-US
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Output format
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