Abstract
Reddit is a community-oriented social network, where users can pose questions, share their own views and experiences within subreddit communities they have subscribed to, with the possibility that other users might view, rate and comment on their posts. A recommender system 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.
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Notes
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The complete source code is available at: https://github.com/Bani57/ subredditRecommender.
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This work was partially financed by the Faculty of Computer Science and Engineering at the “Ss. Cyril and Methodius” University.
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Janchevski, A., Gievska, S. (2019). A Study of Different Models for Subreddit Recommendation Based on User-Community Interaction. In: Gievska, S., Madjarov, G. (eds) ICT Innovations 2019. Big Data Processing and Mining. ICT Innovations 2019. Communications in Computer and Information Science, vol 1110. Springer, Cham. https://doi.org/10.1007/978-3-030-33110-8_9
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