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Sorting the Healthy Diet Signal from the Social Media Expert Noise: Preliminary Evidence from the Healthy Diet Discourse on Twitter
Over 2.8 million people die each year from being overweight or obese, a largely preventable disease. Social media has fundamentally changed the way we communicate, collaborate, consume, and create content. The ease with which content can be shared has resulted in a rapid increase in the number of in...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7698912/ https://www.ncbi.nlm.nih.gov/pubmed/33218105 http://dx.doi.org/10.3390/ijerph17228557 |
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author | Lynn, Theo Rosati, Pierangelo Leoni Santos, Guto Endo, Patricia Takako |
author_facet | Lynn, Theo Rosati, Pierangelo Leoni Santos, Guto Endo, Patricia Takako |
author_sort | Lynn, Theo |
collection | PubMed |
description | Over 2.8 million people die each year from being overweight or obese, a largely preventable disease. Social media has fundamentally changed the way we communicate, collaborate, consume, and create content. The ease with which content can be shared has resulted in a rapid increase in the number of individuals or organisations that seek to influence opinion and the volume of content that they generate. The nutrition and diet domain is not immune to this phenomenon. Unfortunately, from a public health perspective, many of these ‘influencers’ may be poorly qualified in order to provide nutritional or dietary guidance, and advice given may be without accepted scientific evidence and contrary to public health policy. In this preliminary study, we analyse the ‘healthy diet’ discourse on Twitter. While using a multi-component analytical approach, we analyse more than 1.2 million English language tweets over a 16-month period in order to identify and characterise the influential actors and discover topics of interest in the discourse. Our analysis suggests that the discourse is dominated by non-health professionals. There is widespread use of bots that pollute the discourse and seek to create a false equivalence on the efficacy of a particular nutritional strategy or diet. Topic modelling suggests a significant focus on diet, nutrition, exercise, weight, disease, and quality of life. Public health policy makers and professional nutritionists need to consider what interventions can be taken in order to counteract the influence of non-professional and bad actors on social media. |
format | Online Article Text |
id | pubmed-7698912 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-76989122020-11-29 Sorting the Healthy Diet Signal from the Social Media Expert Noise: Preliminary Evidence from the Healthy Diet Discourse on Twitter Lynn, Theo Rosati, Pierangelo Leoni Santos, Guto Endo, Patricia Takako Int J Environ Res Public Health Article Over 2.8 million people die each year from being overweight or obese, a largely preventable disease. Social media has fundamentally changed the way we communicate, collaborate, consume, and create content. The ease with which content can be shared has resulted in a rapid increase in the number of individuals or organisations that seek to influence opinion and the volume of content that they generate. The nutrition and diet domain is not immune to this phenomenon. Unfortunately, from a public health perspective, many of these ‘influencers’ may be poorly qualified in order to provide nutritional or dietary guidance, and advice given may be without accepted scientific evidence and contrary to public health policy. In this preliminary study, we analyse the ‘healthy diet’ discourse on Twitter. While using a multi-component analytical approach, we analyse more than 1.2 million English language tweets over a 16-month period in order to identify and characterise the influential actors and discover topics of interest in the discourse. Our analysis suggests that the discourse is dominated by non-health professionals. There is widespread use of bots that pollute the discourse and seek to create a false equivalence on the efficacy of a particular nutritional strategy or diet. Topic modelling suggests a significant focus on diet, nutrition, exercise, weight, disease, and quality of life. Public health policy makers and professional nutritionists need to consider what interventions can be taken in order to counteract the influence of non-professional and bad actors on social media. MDPI 2020-11-18 2020-11 /pmc/articles/PMC7698912/ /pubmed/33218105 http://dx.doi.org/10.3390/ijerph17228557 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Lynn, Theo Rosati, Pierangelo Leoni Santos, Guto Endo, Patricia Takako Sorting the Healthy Diet Signal from the Social Media Expert Noise: Preliminary Evidence from the Healthy Diet Discourse on Twitter |
title | Sorting the Healthy Diet Signal from the Social Media Expert Noise: Preliminary Evidence from the Healthy Diet Discourse on Twitter |
title_full | Sorting the Healthy Diet Signal from the Social Media Expert Noise: Preliminary Evidence from the Healthy Diet Discourse on Twitter |
title_fullStr | Sorting the Healthy Diet Signal from the Social Media Expert Noise: Preliminary Evidence from the Healthy Diet Discourse on Twitter |
title_full_unstemmed | Sorting the Healthy Diet Signal from the Social Media Expert Noise: Preliminary Evidence from the Healthy Diet Discourse on Twitter |
title_short | Sorting the Healthy Diet Signal from the Social Media Expert Noise: Preliminary Evidence from the Healthy Diet Discourse on Twitter |
title_sort | sorting the healthy diet signal from the social media expert noise: preliminary evidence from the healthy diet discourse on twitter |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7698912/ https://www.ncbi.nlm.nih.gov/pubmed/33218105 http://dx.doi.org/10.3390/ijerph17228557 |
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