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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Palovics, R. Benczur, A.A. |
| Copyright Year | 2013 |
| Description | Author affiliation: Inst. for Comput. Sci. & Control, Hungary (Palovics, R.; Benczur, A.A.) |
| Abstract | Several recent results show the influence of social contacts to spread certain properties over the network, but others question the methodology of these experiments by proposing that the measured effects may be due to homophily or a shared environment. In this paper we justify the existence of the social influence by considering the temporal behavior of Last.fm users. In order to clearly distinguish between friends sharing the same interest, especially since Last.fm recommends friends based on similarity of taste, we separated the timeless effect of similar taste from the temporal impulses of immediately listening to the same artist after a friend. We measured strong increase of listening to a completely new artist in a few hours period after a friend compared to non-friends representing a simple trend or external influence. In our experiment to eliminate network independent elements of taste, we improved collaborative filtering and trend based methods by blending with simple time aware recommendations based on the influence of friends. Our experiments are carried over the two-year “scrobble” history of 70,000 Last.fm users. |
| Sponsorship | IEEE Comput. Soc. |
| Starting Page | 486 |
| Ending Page | 493 |
| File Size | 350699 |
| Page Count | 8 |
| File Format | |
| ISBN | 9781450322409 |
| DOI | 10.1145/2492517.2492532 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2013-08-25 |
| Publisher Place | Canada |
| Access Restriction | Subscribed |
| Rights Holder | ACM and IEEE |
| Subject Keyword | Algorithm design and analysis Social network services Conferences Collaboration Music Delays Recommender systems |
| Content Type | Text |
| Resource Type | Article |
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