Publication details
How to exploit Recommender Systems in Social Media
| Authors | |
|---|---|
| Year of publication | 2018 |
| Type | Article in Proceedings |
| Conference | Proceedings of the IEEE 19th International Conference on Information Reuse and Integration for Data Science |
| MU Faculty or unit | |
| Citation | |
| Doi | http://dx.doi.org/10.1109/IRI.2018.00085 |
| Keywords | social media; recommender system; media recommendations; social media applications |
| Description | The rapid increase and widespread of social media data have created new research challenges and opportunities for social media recommender systems, which are designed to recommend personalized, interesting, credible social media content with possible social impact. However, due to complexity in social network and new media interaction, the research of social media recommender systems is still on its initial stage. Therefore, this paper aims to review the state-of-the-art research that are related to social media recommender systems, and identify the critical factors for building new social media recommender systems. Our results show that relevance, validity, popularity, credibility and social impact are considered to be the 5 important factors for social media recommender systems. |