Kamiński Mikołaj, Fogel Agata, Dylik Adrianna, Kręgielska-Narożna Matylda, Bogdański Paweł
Department of the Treatment of Obesity and Metabolic Disorders, and of Clinical Dietetics, Poznań University of Medical Sciences, Przybyszewskiego 49, 60-355, Poznań, Poland.
Student Scientific Club of Clinical Dietetics, Department of the Treatment of Obesity and Metabolic Disorders, and of Clinical Dietetics, Poznań University of Medical Sciences, Przybyszewskiego 49, 60-355, Poznań, Poland.
Int J Obes (Lond). 2025 Apr;49(4):673-681. doi: 10.1038/s41366-024-01689-y. Epub 2024 Nov 26.
X (formerly Twitter) is a unique social medium where many famous people and health institutions post and interact with casual users. We aimed to explore reactions to tweets about obesity and weight loss from accounts representing celebrities, politicians, sportsmen, and health authorities.
We collected tweets from n = 2444 X profiles representing seven categories: celebrities, politicians, sportsmen, medical specialists, medical journals, medical universities, and health institutions. We retrieved tweets from the accounts and selected tweets about, e.g., obesity, overweight, body mass index, and weight loss. We conducted sentiment analysis, descriptive statistics, and multivariable quantile regression modeling. In quantile regression models, each tau represents a decile from 0.1 to 0.9 of the dependent variable (number of likes or retweets). Therefore, a tau value of 0.5 represents the 5th decile, the 50th percentile, and the median of the dependent variable.
The final dataset consisted of n = 8989 tweets. Achieving a large number of likes (taus 0.7, 0.8, and 0.9) was positively associated with posts written by celebrities, politicians, medical journals, and universities, while it was negatively associated with tweets authored by health institutions or medical specialists. In the case of a significant number of retweets, a positive association was observed for all account types, except for health institutions, for which the relationship was negative. These relationships were independent of verification status, the number of followers, tweet length, and sentiment.
Tweets concerning obesity and weight loss originating from accounts representing health institutions garnered fewer likes and retweets compared to other types of accounts, including non-medical ones. A limitation of the study is the relatively small number of tweets emanating from non-medical accounts. A X informational campaign about obesity should engage non-medical accounts with many followers to reach as many users as possible.
X（前身为推特）是一个独特的社交媒体平台，许多名人及健康机构在此发布内容并与普通用户互动。我们旨在探究代表名人、政治家、运动员和卫生当局的账号发布的有关肥胖和减肥推文的反响。
我们从代表七类人群的n = 2444个X账号中收集推文，这七类人群分别为：名人、政治家、运动员、医学专家、医学期刊、医科大学和卫生机构。我们从这些账号中检索推文，并挑选出例如关于肥胖、超重、体重指数和减肥的推文。我们进行了情感分析、描述性统计和多变量分位数回归建模。在分位数回归模型中，每个τ代表因变量（点赞数或转发数）从0.1到0.9的十分位数。因此，τ值为0.5代表第5个十分位数、第50百分位数以及因变量的中位数。
最终数据集包含n = 8989条推文。获得大量点赞（τ值为0.7、0.8和0.9）与名人、政治家、医学期刊和大学发布的推文呈正相关，而与卫生机构或医学专家发布的推文呈负相关。在转发量显著的情况下，除卫生机构外，所有账号类型均呈现正相关，卫生机构的相关关系为负。这些关系不受认证状态、关注者数量、推文长度和情感的影响。
与包括非医学账号在内的其他类型账号相比，来自卫生机构账号的有关肥胖和减肥的推文获得的点赞和转发较少。本研究的一个局限性是来自非医学账号的推文数量相对较少。X平台关于肥胖的宣传活动应吸引拥有大量关注者的非医学账号，以覆盖尽可能多的用户。
