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http://hdl.handle.net/20.500.12188/16569
Наслов: | A Study of Different Models for Subreddit Recommendation Based on User-Community Interaction | Authors: | Janchevski, Andrej Gievska, Sonja |
Keywords: | Social network analytics · Recommender systems · Data fusion · Network embeddings · Content similarity | Issue Date: | окт-2019 | Publisher: | Springer | Abstract: | Abstract. Reddit is a community-oriented social network, where users can pose questions, share their own views and experiences within subred- dit communities they have subscribed to, with the possibility that other users might view, rate and comment on their posts. A recommender sys- tem plays a crucial role in advancing and steering interactions on social media platforms, and in the case of Reddit, it performs across many levels. This study investigates the potential benefits of social media analytics for improving the quality of recommendations. Five models are proposed and validated, with a particular focus on improving the recommendations of subreddits that might be of interest to a particular user. The results reinforce the notion that capturing and fusing diverse set of features is crucial for confronting the challenges of predicting elusive phenomenon such as user’s preferences and interests. | URI: | http://hdl.handle.net/20.500.12188/16569 | DOI: | DOI: 10.1007/978-3-030-33110-8_9 |
Appears in Collections: | Faculty of Computer Science and Engineering: Conference papers |
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