Analysing Sentiment and Topics Related to Multiple Sclerosis on Twitter

The MIE2020 conference planned end of April 2020 has been cancelled due to the SARS-CoV-2 pandemy Background and objective: Social media could be valuable tools to support people with multiple sclerosis (MS). There is little evidence on the MSrelated topics that are discussed on social media, and the sentiment linked to these topics. The objective of this work is to identify the MS-related main topics discussed on Twitter, and the sentiment linked to them. Methods: Tweets dealing with MS in the English language were extracted. Latent-Dirilecht Allocation (LDA) was used to identify the main topics discussed in these tweets. Iterative inductive process was used to group the tweets into recurrent topics. The sentiment analysis of these tweets was performed using SentiStrength. Results: LDA’ identified topics were grouped into 4 categories, tweets dealing with: related chronic conditions; condition burden; disease-modifying drugs; and awarenessraising. Tweets on condition burden and related chronic conditions were the most negative (p