Connecting the Dots to Infer Followers' Topical Interest on Twitter.

Authors: 
Aastha Nigam, Salvador Aguinaga, and Nitesh V. Chawla.
Citation: 
IEEE International Conference on Behavioral, Economic, and Socio-Cultural Computing (BESC)
Publication Date: 
November, 2016

Twitter provides a platform for information sharing and diffusion, and has quickly emerged as a mechanism for organizations to engage with their consumers. A driving factor for engagement is providing relevant and timely content to users. We posit that the engagement via tweets offers a good potential to discover user interests and leverage that information to target specific content of interest. To that end, we have developed a framework that analyzes tweets to identify the interests of current followers and leverages topic models to deliver a personalized topic profile for each user. We validated our framework by partnering up with a local media company and analyzing the content gap between them and their followers. We also developed a mobile application that incorporates the proposed framework.