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Subject: Social network analytics · Recommender systems · Data fusion · Network embeddings · Content similarity


Year: 2019


Type: Article



Title: A Study of Different Models for Subreddit Recommendation Based on User-Community Interaction


Author: Janchevski, Andrej
Author: Gievska, Sonja



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.


Publisher: Springer


Relation:



Identifier: oai:repository.ukim.mk:20.500.12188/16569
Identifier: http://hdl.handle.net/20.500.12188/16569
Identifier: DOI: 10.1007/978-3-030-33110-8_9



TitleDateViews
A Study of Different Models for Subreddit Recommendation Based on User-Community Interaction201917