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2014 | OriginalPaper | Chapter

iPoll: Automatic Polling Using Online Search

Authors : Thin Nguyen, Dinh Phung, Wei Luo, Truyen Tran, Svetha Venkatesh

Published in: Web Information Systems Engineering – WISE 2014

Publisher: Springer International Publishing

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For years, opinion polls rely on data collected through telephone or person-to-person surveys. The process is costly, inconvenient, and slow. Recently online search data has emerged as potential proxies for the survey data. However considerable human involvement is still needed for the selection of search indices, a task that requires knowledge of both the target issue and how search terms are used by the online community. The robustness of such manually selected search indices can be questionable. In this paper, we propose an automatic polling system through a novel application of machine learning. In this system, the needs for examining, comparing, and selecting search indices have been eliminated through automatic generation of candidate search indices and intelligent combination of the indices. The results include a publicly accessible web application that provides real-time, robust, and accurate measurements of public opinions on several subjects of general interest.

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Metadata
Title
iPoll: Automatic Polling Using Online Search
Authors
Thin Nguyen
Dinh Phung
Wei Luo
Truyen Tran
Svetha Venkatesh
Copyright Year
2014
Publisher
Springer International Publishing
DOI
https://doi.org/10.1007/978-3-319-11749-2_21

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