How Health Information Spreads in Twitter: The Whos and Whats of Philippine TB-data

Abstract

Twitter is a popular platform for disseminating health information. Unfortunately, there is no clear way to monitor how information reaches the intended audiences. This research examined how health information spreads on Twitter and identified factors that affect the spreading within the Philippines. We created a process whose goal is to generate results that experts can deeply analyze to reveal insights into information spread. The process consists of crawling Twitter data, transforming the data and applying sentiment identification and topic modeling, and performing Social Network Analysis (SNA). The SNA graphs allow for the study of the interactions between Twitter users and tweets while giving insights on influential users and topics discussed across clusters. The study explored and utilized tuberculosis-related tweets. Though the algorithms were meant to process tweets written in Filipino, the process is mostly language-agnostic and can be applied to Twitter data. The results also help in identifying strategies that can improve health information spread on Twitter in the Philippines.