Tools and techniques for capturing possible HIV risk-related tweets of Filipinos
College of Computer Studies
International Journal of Scientific and Technology Research
Although the number of HIV cases in the Philippines has been steadily increasing, limited studies have been conducted to mitigate the root cause of this problem. The Department of Health expressed the need to design intervention programs to monitor this epidemic. In this study, researchers explored emerging technologies to generate new data that can be used for further studies. A focus group discussion (FGD) among Persons Living with HIV (PLHIV) was conducted to determine how Filipino Men Having Sex with Men (MSM) communicate with each other online. The most common words produced from the FGD were presented to HIV domain experts and validated. In order to collect quantitative data, tweets were extracted to generate profiles of online interactions. Tweepy, a Python library used in accessing the Twitter Advanced Programming Interface (API), was used to collect tweets and the bounding box tool was used to filter tweets coming from the Philippines. The researchers acknowledged that majority of MSM Twitter users preferred to disable geolocation, other techniques were applied to capture risk-related tweets from Filipino MSMs. MySql was considered to handle the tweet repository. A total of 206,822 tweets were extracted from October 8, 2019 to November 6 of the same year. Among all the tweets collected, there are significant amount of tweets that indicate risk related to HIV. Results indicate that Twitter can be utilized to produce data that the government can use to identify high risk locations that required more attention in terms of HIV intervention. © IJSTR 2020.
Manaloto, A. D., & Raga, R. C. (2020). Tools and techniques for capturing possible HIV risk-related tweets of Filipinos. International Journal of Scientific and Technology Research, 9 (4), 2116-2121. Retrieved from https://animorepository.dlsu.edu.ph/faculty_research/3369
Computational linguistics--Philippines; HIV infections--Philippines; Microblogs--Philippines; Twitter; Global Positioning System