Pinterest Board Recommendation for Twitter Users
This addresses the need for cross-platform content discovery for social media users, but it is incremental as it applies existing methods to a new context.
The paper tackled the problem of recommending Pinterest boards to Twitter users by mapping Twitter followees to pinboard topics using MultiLabel classification and visual diversification, with a preliminary experiment on 2000 users validating the system.
Pinboard on Pinterest is an emerging media to engage online social media users, on which users post online images for specific topics. Regardless of its significance, there is little previous work specifically to facilitate information discovery based on pinboards. This paper proposes a novel pinboard recommendation system for Twitter users. In order to associate contents from the two social media platforms, we propose to use MultiLabel classification to map Twitter user followees to pinboard topics and visual diversification to recommend pinboards given user interested topics. A preliminary experiment on a dataset with 2000 users validated our proposed system.