Antonino Angi
Applying Natural Language Processing techniques to analyze HIV-related discussions on Social Media.
Rel. Paolo Garza. Politecnico di Torino, Corso di laurea magistrale in Ingegneria Informatica (Computer Engineering), 2020
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Abstract
Nowadays social media are being used to monitor the progress of viruses and share important prevention and treatment information. This has also allowed the creation of a community of people united by the same disease, to give themselves strength, comfort and advice. The objective of this work is to extract and understand discussions about HIV on a popular social media platform: Twitter, a micro-blogging application. Tweets with the hashtag #HIV were collected in the date range of one year, starting from November 12th 2018 to November 12th 2019. They were then filtered and cleaned using NLP techniques, which allowed the removal of duplicates, non-english texts and useless information, such as tweets only containing urls, mentions or hashtags.
After the cleaning phase, the main analyzes carried out were sentiment analysis and content analysis which, using data mining and text mining algorithms were able to reveal their emotions and the most influential topics written about HIV
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