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Learning to un-rank : quantifying search exposure for users in online communities
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Biega, J. Asia , Ghazimatin, Azin , Ferhatosmanoglu, Hakan , Gummadi , Krishna P. and Weikum, Gerhard (2017) Learning to un-rank : quantifying search exposure for users in online communities. In: CIKM 2017 : The 26th 2017 ACM Conference on Information and Knowledge Management, Singapore, 6-10 Nov 2017. Published in: Proceedings of the 26th International Conference on Information and Knowledge Management (CIKM) 267-276 . ISBN 9781450349185 .
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WRAP-learning-un-rank-quantifying-exposure-communities-Ferhatosmanoglu-2017.pdf - Accepted Version - Requires a PDF viewer. Download (1078Kb) | Preview |
Official URL: https://doi.org/10.1145/3132847.3133040
Abstract
Search engines in online communities such as Twitter or Facebook not only return matching posts, but also provide links to the profiles of the authors. Thus, when a user appears in the top-k results for a sensitive keyword query, she becomes widely exposed in a sensitive context. The effects of such exposure can result in a serious privacy violation, ranging from embarrassment all the way to becoming a victim of organizational discrimination.
In this paper, we propose the first model for quantifying search exposure on the service provider side, casting it into a reverse k-nearest-neighbor problem. Moreover, since a single user can be exposed by a large number of queries, we also devise a learning-to-rank method for identifying the most critical queries and thus making the warnings user-friendly. We develop efficient algorithms, and present experiments with a large number of user profiles from Twitter that demonstrate the practical viability and effectiveness of our framework.
| Item Type: | Conference Item (Paper) | |||||||||
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| Subjects: | T Technology > TK Electrical engineering. Electronics Nuclear engineering | |||||||||
| Divisions: | Faculty of Science > Computer Science | |||||||||
| Library of Congress Subject Headings (LCSH): | Search engines -- Programming, Information retrieval, Twitter (Firm) | |||||||||
| Journal or Publication Title: | Proceedings of the 26th International Conference on Information and Knowledge Management (CIKM) | |||||||||
| Publisher: | ACM | |||||||||
| ISBN: | 9781450349185 | |||||||||
| Official Date: | 5 August 2017 | |||||||||
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| Page Range: | 267-276 | |||||||||
| Status: | Peer Reviewed | |||||||||
| Publication Status: | Published | |||||||||
| Access rights to Published version: | Restricted or Subscription Access | |||||||||
| RIOXX Funder/Project Grant: |
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| Conference Paper Type: | Paper | |||||||||
| Title of Event: | CIKM 2017 : The 26th 2017 ACM Conference on Information and Knowledge Management | |||||||||
| Type of Event: | Conference | |||||||||
| Location of Event: | Singapore | |||||||||
| Date(s) of Event: | 6-10 Nov 2017 |
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