Abstract
Liking or marking an object, event, or resource as a favorite is one of the most pervasive actions in social media. This particular action plays an important role in platforms in which a lot of content is shared. In this paper we take a large sample of users in Flickr and analyze logs of their favorite actions considering factors such as time period, type of connection with the owner of the photo, and other aspects. The objective of our work is, on one hand to gain insights into the “liking” behavior in social media, and on the other hand, to inform strategies for recommending items users may like. We place particular focus on analyzing the relationship between recent photos uploaded by user’s connections and the favorite action, noting that a direct application of our work would lead to algorithms for recommending users a subset of these “recently uploaded” photos that they might favorite. We compare several features derived from our analysis, in terms of how effective they might be in retrieving favorite photographs.
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Lipczak, M., Trevisiol, M., Jaimes, A. (2013). Analyzing Favorite Behavior in Flickr. In: Li, S., et al. Advances in Multimedia Modeling. MMM 2013. Lecture Notes in Computer Science, vol 7732. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35725-1_49
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DOI: https://doi.org/10.1007/978-3-642-35725-1_49
Publisher Name: Springer, Berlin, Heidelberg
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