Analyzing, Detecting, and Exploiting Sentiment in Web Queries

Date

2013-12-01

Author

Chelaru, Sergiu
Altıngövde, İsmail Sengör
Siersdorfer, Stefan
Nejdl, Wolfgang

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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The Web contains an increasing amount of biased and opinionated documents on politics, products, and polarizing events. In this article, we present an indepth analysis of Web search queries for controversial topics, focusing on query sentiment. To this end, we conduct extensive user assessments and discriminative term analyses, as well as a sentiment analysis using the SentiWordNet thesaurus, a lexical resource containing sentiment annotations. Furthermore, in order to detect the sentiment expressed in queries, we build different classifiers based on query texts, query result titles, and snippets. We demonstrate the virtue of query sentiment detection in two different use cases. First, we define a query recommendation scenario that employs sentiment detection of results to recommend additional queries for polarized queries issued by search engine users. The second application scenario is controversial topic discovery, where query sentiment classifiers are employed to discover previously unknown topics that trigger both highly positive and negative opinions among the users of a search engine. For both use cases, the results of our evaluations on real-world data are promising and show the viability and potential of query sentiment analysis in practical scenarios.

Subject Keywords

Computer Networks and Communications

URI

https://hdl.handle.net/11511/35583

Journal

ACM TRANSACTIONS ON THE WEB

DOI

https://doi.org/10.1145/2535525

Collections

Department of Computer Engineering, Article

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Citation Formats

S. Chelaru, İ. S. Altıngövde, S. Siersdorfer, and W. Nejdl, “Analyzing, Detecting, and Exploiting Sentiment in Web Queries,” ACM TRANSACTIONS ON THE WEB, pp. 0–0, 2013, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/35583.