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Diabetes Topics Associated With Engagement on Twitter
INTRODUCTION: Social media are widely used by the general public and by public health and health care professionals. Emerging evidence suggests engagement with public health information on social media may influence health behavior. However, the volume of data accumulating daily on Twitter and other...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Centers for Disease Control and Prevention
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4436046/ https://www.ncbi.nlm.nih.gov/pubmed/25950569 http://dx.doi.org/10.5888/pcd12.140402 |
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author | Harris, Jenine K. Mart, Adelina Moreland-Russell, Sarah Caburnay, Charlene A. |
author_facet | Harris, Jenine K. Mart, Adelina Moreland-Russell, Sarah Caburnay, Charlene A. |
author_sort | Harris, Jenine K. |
collection | PubMed |
description | INTRODUCTION: Social media are widely used by the general public and by public health and health care professionals. Emerging evidence suggests engagement with public health information on social media may influence health behavior. However, the volume of data accumulating daily on Twitter and other social media is a challenge for researchers with limited resources to further examine how social media influence health. To address this challenge, we used crowdsourcing to facilitate the examination of topics associated with engagement with diabetes information on Twitter. METHODS: We took a random sample of 100 tweets that included the hashtag “#diabetes” from each day during a constructed week in May and June 2014. Crowdsourcing through Amazon’s Mechanical Turk platform was used to classify tweets into 9 topic categories and their senders into 3 Twitter user categories. Descriptive statistics and Tweedie regression were used to identify tweet and Twitter user characteristics associated with 2 measures of engagement, “favoriting” and “retweeting.” RESULTS: Classification was reliable for tweet topics and Twitter user type. The most common tweet topics were medical and nonmedical resources for diabetes. Tweets that included information about diabetes-related health problems were positively and significantly associated with engagement. Tweets about diabetes prevalence, nonmedical resources for diabetes, and jokes or sarcasm about diabetes were significantly negatively associated with engagement. CONCLUSION: Crowdsourcing is a reliable, quick, and economical option for classifying tweets. Public health practitioners aiming to engage constituents around diabetes may want to focus on topics positively associated with engagement. |
format | Online Article Text |
id | pubmed-4436046 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Centers for Disease Control and Prevention |
record_format | MEDLINE/PubMed |
spelling | pubmed-44360462015-06-02 Diabetes Topics Associated With Engagement on Twitter Harris, Jenine K. Mart, Adelina Moreland-Russell, Sarah Caburnay, Charlene A. Prev Chronic Dis Original Research INTRODUCTION: Social media are widely used by the general public and by public health and health care professionals. Emerging evidence suggests engagement with public health information on social media may influence health behavior. However, the volume of data accumulating daily on Twitter and other social media is a challenge for researchers with limited resources to further examine how social media influence health. To address this challenge, we used crowdsourcing to facilitate the examination of topics associated with engagement with diabetes information on Twitter. METHODS: We took a random sample of 100 tweets that included the hashtag “#diabetes” from each day during a constructed week in May and June 2014. Crowdsourcing through Amazon’s Mechanical Turk platform was used to classify tweets into 9 topic categories and their senders into 3 Twitter user categories. Descriptive statistics and Tweedie regression were used to identify tweet and Twitter user characteristics associated with 2 measures of engagement, “favoriting” and “retweeting.” RESULTS: Classification was reliable for tweet topics and Twitter user type. The most common tweet topics were medical and nonmedical resources for diabetes. Tweets that included information about diabetes-related health problems were positively and significantly associated with engagement. Tweets about diabetes prevalence, nonmedical resources for diabetes, and jokes or sarcasm about diabetes were significantly negatively associated with engagement. CONCLUSION: Crowdsourcing is a reliable, quick, and economical option for classifying tweets. Public health practitioners aiming to engage constituents around diabetes may want to focus on topics positively associated with engagement. Centers for Disease Control and Prevention 2015-05-07 /pmc/articles/PMC4436046/ /pubmed/25950569 http://dx.doi.org/10.5888/pcd12.140402 Text en https://creativecommons.org/licenses/by/4.0/This is a publication of the U.S. Government. This publication is in the public domain and is therefore without copyright. All text from this work may be reprinted freely. Use of these materials should be properly cited. |
spellingShingle | Original Research Harris, Jenine K. Mart, Adelina Moreland-Russell, Sarah Caburnay, Charlene A. Diabetes Topics Associated With Engagement on Twitter |
title | Diabetes Topics Associated With Engagement on Twitter |
title_full | Diabetes Topics Associated With Engagement on Twitter |
title_fullStr | Diabetes Topics Associated With Engagement on Twitter |
title_full_unstemmed | Diabetes Topics Associated With Engagement on Twitter |
title_short | Diabetes Topics Associated With Engagement on Twitter |
title_sort | diabetes topics associated with engagement on twitter |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4436046/ https://www.ncbi.nlm.nih.gov/pubmed/25950569 http://dx.doi.org/10.5888/pcd12.140402 |
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