A large-scale sentiment analysis for Yahoo! Answers

Onur Kucuktunc, B. Barla Cambazoglu, Ingmar Weber, Hakan Ferhatosmanoglu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

88 Citations (Scopus)

Abstract

Sentiment extraction from online web documents has recently been an active research topic due to its potential use in commercial applications. By sentiment analysis, we refer to the problem of assigning a quantitative positive/negative mood to a short bit of text. Most studies in this area are limited to the identification of sentiments and do not investigate the interplay between sentiments and other factors. In this work, we use a sentiment extraction tool to investigate the influence of factors such as gender, age, education level, the topic at hand, or even the time of the day on sentiments in the context of a large online question answering site. We start our analysis by looking at direct correlations, e.g., we observe more positive sentiments on weekends, very neutral ones in the Science & Mathematics topic, a trend for younger people to express stronger sentiments, or people in military bases to ask the most neutral questions. We then extend this basic analysis by investigating how properties of the (asker, answerer) pair affect the sentiment present in the answer. Among other things, we observe a dependence on the pairing of some inferred attributes estimated by a user's ZIP code. We also show that the best answers differ in their sentiments from other answers, e.g., in the Business & Finance topic, best answers tend to have a more neutral sentiment than other answers. Finally, we report results for the task of predicting the attitude that a question will provoke in answers. We believe that understanding factors influencing the mood of users is not only interesting from a sociological point of view, but also has applications in advertising, recommendation, and search.

Original languageEnglish
Title of host publicationWSDM 2012 - Proceedings of the 5th ACM International Conference on Web Search and Data Mining
Pages633-642
Number of pages10
DOIs
Publication statusPublished - 15 Mar 2012
Externally publishedYes
Event5th ACM International Conference on Web Search and Data Mining, WSDM 2012 - Seattle, WA, United States
Duration: 8 Feb 201212 Feb 2012

Other

Other5th ACM International Conference on Web Search and Data Mining, WSDM 2012
CountryUnited States
CitySeattle, WA
Period8/2/1212/2/12

Fingerprint

Military bases
Finance
Marketing
Education
Industry

Keywords

  • Attitude
  • Collaborative question answering
  • Prediction
  • Sentiment analysis
  • Sentimentality

ASJC Scopus subject areas

  • Computer Networks and Communications

Cite this

Kucuktunc, O., Cambazoglu, B. B., Weber, I., & Ferhatosmanoglu, H. (2012). A large-scale sentiment analysis for Yahoo! Answers. In WSDM 2012 - Proceedings of the 5th ACM International Conference on Web Search and Data Mining (pp. 633-642) https://doi.org/10.1145/2124295.2124371

A large-scale sentiment analysis for Yahoo! Answers. / Kucuktunc, Onur; Cambazoglu, B. Barla; Weber, Ingmar; Ferhatosmanoglu, Hakan.

WSDM 2012 - Proceedings of the 5th ACM International Conference on Web Search and Data Mining. 2012. p. 633-642.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Kucuktunc, O, Cambazoglu, BB, Weber, I & Ferhatosmanoglu, H 2012, A large-scale sentiment analysis for Yahoo! Answers. in WSDM 2012 - Proceedings of the 5th ACM International Conference on Web Search and Data Mining. pp. 633-642, 5th ACM International Conference on Web Search and Data Mining, WSDM 2012, Seattle, WA, United States, 8/2/12. https://doi.org/10.1145/2124295.2124371
Kucuktunc O, Cambazoglu BB, Weber I, Ferhatosmanoglu H. A large-scale sentiment analysis for Yahoo! Answers. In WSDM 2012 - Proceedings of the 5th ACM International Conference on Web Search and Data Mining. 2012. p. 633-642 https://doi.org/10.1145/2124295.2124371
Kucuktunc, Onur ; Cambazoglu, B. Barla ; Weber, Ingmar ; Ferhatosmanoglu, Hakan. / A large-scale sentiment analysis for Yahoo! Answers. WSDM 2012 - Proceedings of the 5th ACM International Conference on Web Search and Data Mining. 2012. pp. 633-642
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