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Title: Assessing Candidate Preference through Web Browsing History
Predicting election outcomes is of considerable interest to candidates, political scientists, and the public at large. We propose the use of Web browsing history as a new indicator of candidate preference among the electorate, one that has potential to overcome a number of the drawbacks of election polls. However, there are a number of challenges that must be overcome to effectively use Web browsing for assessing candidate preference—including the lack of suitable ground truth data and the heterogeneity of user populations in time and space. We address these challenges, and show that the resulting methods can shed considerable light on the dynamics of voters’ candidate preferences in ways that are difficult to achieve using polls.  more » « less
Award ID(s):
1703592
NSF-PAR ID:
10096153
Author(s) / Creator(s):
; ; ; ;
Date Published:
Journal Name:
24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining
Page Range / eLocation ID:
158 to 167
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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