Modeling the influence of popular trending events on user search behavior

Shubhra Kanti Karmaker Santu, Liangda Li, Dae Hoon Park, Yi Chang, Chengxiang Zhai

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

Abstract

Understanding how users' search behavior is influenced by real world events is important both for social science research and for designing better search engines for users. In this paper, we study how to model the influence of events on user queries by framing it as a novel data mining problem. Specifically, given a text description of an event, we mine the search log data to identify queries that are triggered by it and further characterize the temporal trend of influence created by the same event on user queries. We solve this data mining problem by proposing computational measures that quantify the influence of an event on a query to identify triggered queries and then, proposing a novel extension of Hawkes process to model the evolutionary trend of the influence of an event on search queries. Evaluation results using news articles and search log data show that the proposed approach is effective for identification of queries triggered by events reported in news articles and characterization of the influence trend over time, opening up many interesting opportunities of applications such as comparative analysis of influential events and prediction of event-triggered queries by users.

Original languageEnglish (US)
Title of host publication26th International World Wide Web Conference 2017, WWW 2017 Companion
PublisherInternational World Wide Web Conferences Steering Committee
Pages535-544
Number of pages10
ISBN (Electronic)9781450349147
DOIs
StatePublished - Jan 1 2019
Event26th International World Wide Web Conference, WWW 2017 Companion - Perth, Australia
Duration: Apr 3 2017Apr 7 2017

Other

Other26th International World Wide Web Conference, WWW 2017 Companion
CountryAustralia
CityPerth
Period4/3/174/7/17

Fingerprint

Data mining
Social sciences
Search engines

ASJC Scopus subject areas

  • Software
  • Computer Networks and Communications

Cite this

Santu, S. K. K., Li, L., Park, D. H., Chang, Y., & Zhai, C. (2019). Modeling the influence of popular trending events on user search behavior. In 26th International World Wide Web Conference 2017, WWW 2017 Companion (pp. 535-544). International World Wide Web Conferences Steering Committee. https://doi.org/10.1145/3041021.3054188

Modeling the influence of popular trending events on user search behavior. / Santu, Shubhra Kanti Karmaker; Li, Liangda; Park, Dae Hoon; Chang, Yi; Zhai, Chengxiang.

26th International World Wide Web Conference 2017, WWW 2017 Companion. International World Wide Web Conferences Steering Committee, 2019. p. 535-544.

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

Santu, SKK, Li, L, Park, DH, Chang, Y & Zhai, C 2019, Modeling the influence of popular trending events on user search behavior. in 26th International World Wide Web Conference 2017, WWW 2017 Companion. International World Wide Web Conferences Steering Committee, pp. 535-544, 26th International World Wide Web Conference, WWW 2017 Companion, Perth, Australia, 4/3/17. https://doi.org/10.1145/3041021.3054188
Santu SKK, Li L, Park DH, Chang Y, Zhai C. Modeling the influence of popular trending events on user search behavior. In 26th International World Wide Web Conference 2017, WWW 2017 Companion. International World Wide Web Conferences Steering Committee. 2019. p. 535-544 https://doi.org/10.1145/3041021.3054188
Santu, Shubhra Kanti Karmaker ; Li, Liangda ; Park, Dae Hoon ; Chang, Yi ; Zhai, Chengxiang. / Modeling the influence of popular trending events on user search behavior. 26th International World Wide Web Conference 2017, WWW 2017 Companion. International World Wide Web Conferences Steering Committee, 2019. pp. 535-544
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