Abstract
Social media recommendation is foreseen to be one of the most important services to recommend personalized contents to users in online social network. It imposes great challenge due to the dynamical behavior of users and the large-scale volumes of contents generated by the users. In this chapter, we first present the principal concept of social media recommendation. Then we present the framework of social media recommendation, with a focus on two important types of recommendations: interest-oriented social media recommendation and influence-oriented social media recommendation. For each case, we present the design of the recommendation that takes both social property and content property into account, such as user relations, content similarities, and propagation patterns. Furthermore, we present theoretical results and observations on the social media recommendation approaches.
Keywords
- Social Media Recommendation
- Online Social Networks
- Content-specific Factors
- Influence Maximization Problem
- Item Content
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Wang, Z., Zhu, W., Cui, P., Sun, L., Yang, S. (2013). Social Media Recommendation. In: Ramzan, N., van Zwol, R., Lee, JS., Clüver, K., Hua, XS. (eds) Social Media Retrieval. Computer Communications and Networks. Springer, London. https://doi.org/10.1007/978-1-4471-4555-4_2
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