Accepted for/Published in: JMIR Infodemiology
Date Submitted: Mar 25, 2022
Date Accepted: Jan 10, 2023
Characterizing the discourse of popular diets: Social network analysis to describe information dispersal, identify leading voices, interaction, and themes of mental health
ABSTRACT
Background:
Social media has transformed the way health messages are communicated, and provides the ideal platform to share nutrition information, for communities to connect and for information to spread.
Objective:
This study aimed to characterise the online discourse of popular diets, to describe information dissemination, identify influential voices, explore interactions between community networks, and themes of mental health.
Methods:
This exploratory study utilized Twitter social media posts for an online social network analysis. Popular diet keywords were systematically developed, and data were collected and analyzed using the NodeXL metrics tool to determine key network metrics (vertices, edges, cluster algorithms, graph visualisation, centrality measures, text-analysis and time-series analytics).
Results:
The vegan and ketogenic diets had the largest networks, and the zone diet the smallest. Thirty-one percent (n=54) of the top users endorsed the corresponding diet, and 11% (n=19) claimed a health and/or science education. Complete fragmentation and hub and spoke messaging were the dominant network structures. Eleven of the 16 networks interacted, where the ketogenic diet was mentioned most, with depression and anxiety, and eating disorder words most prominent in the ‘zone diet’ network, and the least prominent in the ‘soy free’, and vegan, ‘dairy free’ and ‘gluten free’ diet networks.
Conclusions:
Social media activity reflects diet trends and provides a platform for nutrition information to spread through re-sharing. A longitudinal exploration of popular diet networks is needed to further understand the impact social media can have on dietary choices. Social media training is vital, and nutrition professionals need to work together as a community to actively re-share evidence-based posts online.
Citation
Per the author's request the PDF is not available.
Copyright
© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.