Social media could be valuable tools to support people with multiple sclerosis (MS). There is little evidence on the MS-related 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.
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.
LDA’ identified topics were grouped into 4 categories, tweets dealing with: related chronic conditions; condition burden; disease-modifying drugs; and awareness-raising. Tweets on condition burden and related chronic conditions were the most negative (p<0.001). A significant lower positive sentiment was found for both tweets dealing with disease-modifying drugs, condition burden, and related chronic conditions (p<0.001). Only tweets on awareness-raising were most positive than the average (p<0.001).
The use of both tools to identify the main discussed topics on social media and to analyse the sentiment of these topics, increases the knowledge of the themes that could represent the bigger burden for persons affected with MS. This knowledge can help to improve support and therapeutic approaches addressed to them.
IOS Press, Inc.
6751 Tepper Drive
Clifton, VA 20124
Tel.: +1 703 830 6300
Fax: +1 703 830 2300 firstname.lastname@example.org
(Corporate matters and books only) IOS Press c/o Accucoms US, Inc.
For North America Sales and Customer Service
West Point Commons
Lansdale PA 19446
Tel.: +1 866 855 8967
Fax: +1 215 660 5042 email@example.com