False-Name-Proof Recommendations in Social Networks
We study the problem of finding a recommendation for an uninformed user in a social network by weighting and aggregating the opinions offered by the informed users in the network. In social networks, an informed user may try to manipulate the recommendation by performing a false-name manipulation, w...
| Main Authors: | , , , |
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| Format: | Conference item |
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Association for Computing Machinery
2016
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| _version_ | 1826273354955358208 |
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| author | Brill, M Freeman, R Conitzer, V Shah, N |
| author_facet | Brill, M Freeman, R Conitzer, V Shah, N |
| author_sort | Brill, M |
| collection | OXFORD |
| description | We study the problem of finding a recommendation for an uninformed user in a social network by weighting and aggregating the opinions offered by the informed users in the network. In social networks, an informed user may try to manipulate the recommendation by performing a false-name manipulation, wherein the user submits multiple opinions through fake accounts. To that end, we impose a no harm axiom: false-name manipulations by a user should not reduce the weight of other users in the network. We show that this axiom has deep connections to false-name-proofness. While it is impossible to design a mechanism that is best for every network subject to this axiom, we propose an intuitive mechanism LEGIT+, and show that it is uniquely optimized for small networks. Using real-world datasets, we show that our mechanism performs very well compared to two baseline mechanisms in a number of metrics, even on large networks. |
| first_indexed | 2024-03-06T22:26:55Z |
| format | Conference item |
| id | oxford-uuid:56f6af93-a140-4aba-8d77-3060be2868cf |
| institution | University of Oxford |
| last_indexed | 2024-03-06T22:26:55Z |
| publishDate | 2016 |
| publisher | Association for Computing Machinery |
| record_format | dspace |
| spelling | oxford-uuid:56f6af93-a140-4aba-8d77-3060be2868cf2022-03-26T16:53:42ZFalse-Name-Proof Recommendations in Social NetworksConference itemhttp://purl.org/coar/resource_type/c_5794uuid:56f6af93-a140-4aba-8d77-3060be2868cfSymplectic Elements at OxfordAssociation for Computing Machinery2016Brill, MFreeman, RConitzer, VShah, NWe study the problem of finding a recommendation for an uninformed user in a social network by weighting and aggregating the opinions offered by the informed users in the network. In social networks, an informed user may try to manipulate the recommendation by performing a false-name manipulation, wherein the user submits multiple opinions through fake accounts. To that end, we impose a no harm axiom: false-name manipulations by a user should not reduce the weight of other users in the network. We show that this axiom has deep connections to false-name-proofness. While it is impossible to design a mechanism that is best for every network subject to this axiom, we propose an intuitive mechanism LEGIT+, and show that it is uniquely optimized for small networks. Using real-world datasets, we show that our mechanism performs very well compared to two baseline mechanisms in a number of metrics, even on large networks. |
| spellingShingle | Brill, M Freeman, R Conitzer, V Shah, N False-Name-Proof Recommendations in Social Networks |
| title | False-Name-Proof Recommendations in Social Networks |
| title_full | False-Name-Proof Recommendations in Social Networks |
| title_fullStr | False-Name-Proof Recommendations in Social Networks |
| title_full_unstemmed | False-Name-Proof Recommendations in Social Networks |
| title_short | False-Name-Proof Recommendations in Social Networks |
| title_sort | false name proof recommendations in social networks |
| work_keys_str_mv | AT brillm falsenameproofrecommendationsinsocialnetworks AT freemanr falsenameproofrecommendationsinsocialnetworks AT conitzerv falsenameproofrecommendationsinsocialnetworks AT shahn falsenameproofrecommendationsinsocialnetworks |