Name
Abstract | ||
|---|---|---|
Users face many choices on the web when it comes to choosing which product to buy, which video to watch, and so on. In making adoption decisions, users rely not only on their own preferences, but also on friends. We call the latter social correlation, which may be caused by the homophily and social influence effects. In this paper, we focus on modeling social correlation on users item adoptions. Given a user-user social graph and an item-user adoption graph, our research seeks to answer the following questions: Whether the items adopted by a user correlate with items adopted by her friends, and how to model item adoptions using social correlation. We propose a social correlation framework that considers a social correlation matrix representing the degrees of correlation from every user to the users friends, in addition to a set of latent factors representing topics of interests of individual users. Based on the framework, we develop two generative models, namely sequential and unified, and the corresponding parameter estimation approaches. From each model, we devise the social correlation only and hybrid methods for predicting missing adoption links. Experiments on LiveJournal and Epinions data sets show that our proposed models outperform the approach based on latent factors only (LDA). |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1109/TKDE.2012.137 | IEEE Trans. Knowl. Data Eng. |
Keywords | Field | DocType |
social correlation,users friend,social correlation matrix,generative models,social influence effect,adoption decision,users item adoption,latent factor,user-user social graph,social correlation framework,latter social correlation,information technology,correlation matrix,internet,parameter estimation,collaboration,database management,social influence,social networks,sparse matrices,data models,data mining,graph theory,correlation,information system | Graph theory,Data mining,Data modeling,Social network,Social graph,Homophily,Computer science,Social influence,Correlation,Artificial intelligence,Machine learning,The Internet | Journal |
Volume | Issue | ISSN |
25 | 9 | 1041-4347 |
Citations | PageRank | References |
19 | 0.74 | 25 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Freddy Chong Tat Chua | 1 | 113 | 8.70 |
| Hady Wirawan Lauw | 2 | 809 | 57.64 |
| Ee-Peng Lim | 3 | 5889 | 754.17 |