Tweeting about fatphobia and body shaming: A retrospective infodemiological study.

ABSTRACT

BACKGROUND: We aimed to analyze reactions to tweets that employed weight-based discrimination terms and to compare them to others posted by the same users on X (formerly Twitter). METHODS: We collected tweets featuring weight-based discrimination terms (the study group) and created a control group by randomly selecting up to five tweets from each account that did not mention any such terms. Descriptive statistics, sentiment analysis, and logistic regression modeling were used to compare the numbers of likes and retweets of the study and control groups, and to understand the emotions associated with these tweets. RESULTS: Our analysis included 22,075 study group tweets and 50,341 control group tweets. Sentiment analysis was conducted on 41,403 (57.2%) tweets, with 65.7% of the study group tweets being found to contain negative sentiments. The study group had a higher median of likes (1 [0-4]) and retweets (0 [0-0]) than the control group (1 [0-2] and 0 [0-0], respectively, with the study group obtaining higher mean ranks in both comparisons, P < 0.001). Multivariable logistic regression analysis revealed that tweets using weight-based discrimination terms gained more likes (OR = 1.22; 95% CI 1.16-1.28) and retweets (OR = 1.61; 95% CI 1.49-1.74), independent of, for example, verification status, follower count, year and season of the tweet, and emotional expression of the tweet. CONCLUSIONS: Tweets concerning fatphobia, body shaming, and similar terms gain more reactions than others posted by the same accounts.