Akademik Veri Yönetim Sistemi
Chronic Illness, 2026 (SCI-Expanded, SSCI, Scopus)
Objectives: The aim is to uncover the perspectives of Twitter users on Multiple Sclerosis (MS) in English tweets by: (i) determining the sentiment of the text (ii) identifying the discussed topics. Methods: The tweets were scanned in April 2023 using the keywords “multiple sclerosis, multiplesclerosis”. Artificial intelligence-based sentiment analysis was conducted on a total of 1168 tweets and content analysis was performed on 17.4% of these tweets. Results: Tweets of 44% are positive and 22.3% are negative sentiment. As a result of content analysis, three themes and their sub-themes were identified: (i) announcement sharing: invitation to support, promotion of academic publications, (ii) information sharing: information providers, information seekers, news providers, (iii) experience sharing: challenging MS, facilitated MS, emotionally impactful MS, comparative MS, misunderstood MS. Subjective content such as experiences is shared less frequently compared to objective content such as announcements and information. Discussion: The findings of this study can serve as a guiding factor in supporting positive views, managing negative views, and promoting the expression of subjective experiences.