A content-location-aware public welfare activity information push system based on microblog. Issue 1 (January 2020) - Chen, Ling
Highlights: Propose a content-location-aware public welfare activity information push system based on microblog. Propose a topic model and keyword search based method to discover users who are explicitly interested in public welfare activity information. Propose a distance metric learning based method to obtain a certain number of local potential users. Abstract: Microblog has become a widely used social media tool, which can help users publish or obtain Public Welfare Activity (PWA) information. Due to the characteristics of large-scale and arbitrary in microblog use, a large amount of messy information is produced, which makes it difficult to discover interesting PWA information. Thus, developing a push system, which can seek a certain number of local potential users for a PWA to be Pushed (PWAP), would be a great help. However, it is challenging to discover users explicitly interested in PWAs and obtain a certain number of local potential users. In this paper, a Content-Location-Aware PWA information Push system based on microblog (CLAP) is proposed, which can seek a certain number of local potential users for a PWAP from massive microblog users, and push the corresponding information to them. Specifically, a topic model and keyword search based method is firstly utilized to discover users who are explicitly interested in the PWAP (i.e., seed users). Secondly, a distance metric learning based method is utilized to obtain a certain number of local potential users by measuring the similarities between seed users and local users. Experimental results demonstrate that the proposed system has a potential to generate superior results.