Communication About Childhood Obesity on Twitter

Abstract

Objectives Childhood obesity more than doubled in the last 20 years, suggesting a need for evidence-based public health strategies. The use of social media to share health information is increasing among the public and public health professionals. However, little is known about the use of social media as a tool for health communication. We used a mixed-methods design to examine communication about childhood obesity on Twitter. Methods NodeXL was used to collect tweets sent in June 2013 containing the hashtag #childhoodobesity. Tweets were coded for content; tweeters were classified by sector and health focus. The network of follower connections among the tweeters was also collected. We used descriptive statistics and exponential random graph modeling to examine tweet content, tweeter characteristics, and the composition and structure of the network of connections facilitating communication among the tweeters. Results We collected 1,110 tweets originating from 576 unique Twitter users. More individuals (65.6%) than organizations (32.9%) tweeted. Tweets were more likely to focus on individual behavior than environment or policy as a cause of, and strategy to combat, childhood obesity. Few government and educational tweeters were in the network. Network members affiliated with government and media were more likely than private individuals to be followed by others in the network, suggesting an important dissemination role. Conclusion There is an opportunity to better disseminate evidence-based information to a broad audience through Twitter by increasing the presence of credible sources in the #childhoodobesity conversation and focusing the content of tweets on scientific evidence.

Messengers and Messages for Tweets That Used #thinspo and #fitspo Hashtags in 2016

“…We used 2-level negative binomial regression to predict retweeting and likes and 2-level logistic regression to predict replies. Models included Twitter user-level and tweet-level characteristics associated with retweeting, liking, and replying to tweets (ie, engaging with tweets) in prior studies, including number of tweets and followers (9) and the type of Twitter user (30). Although hashtag and URL inclusion in a tweet influences engagement (9), all tweets included at least one hashtag because of the method of data collection, and none of the #thinspo tweets included URLs, so we did not include hashtag or URL variables in the models.…”

Assessing the Viability of Social Media for Disseminating Evidence-Based Nutrition Practice Guideline Through Content Analysis of Twitter Messages and Health Professional Interviews: An Observational Study

“…Our method was loosely based on the one described by Step et al and similar to that described by Harris et al, particularly in the use of tracking a single hashtag [9,11]. Tweets that included “#heartfailure” were downloaded from Twittonomy.…”

“…Previous research has successfully used social media meta-data to describe the use and perceptions of health topics such as the use of little cigars and cigarillos [9], breast cancer [10], and pediatric obesity [11]. One of the characteristics of social media is its interactivity and the potential to engage a broad range of users in a dynamic conversation [8].…”

Detecting themes of public concern: A text mining analysis of the Centers for Disease Control and Prevention's Ebola live Twitter chat

“…[3][4][5][6] Text mining of social media data has been used to detect and track diseases, 7,8 natural disasters, 3,9 and life-threatening events, 6,10 as well as to estimate public knowledge concerning health issues. 5,11,12 During crises, social media can serve as crucial communication channels or catalysts for public panic with a proliferation of unmoderated comments. 10 The informal, nonhierarchical nature of Twitter encourages "just-in-time" social connections, the spread of valuable information, and is often relied upon as a source for timely news.…”