| Title |
Obesity in social media: a mixed methods analysis
|
|---|---|
| Published in |
Translational Behavioral Medicine, March 2014
|
| DOI | 10.1007/s13142-014-0256-1 |
| Pubmed ID | |
| Authors |
Wen-ying Sylvia Chou, Abby Prestin, Stephen Kunath |
| Abstract |
The escalating obesity rate in the USA has made obesity prevention a top public health priority. Recent interventions have tapped into the social media (SM) landscape. To leverage SM in obesity prevention, we must understand user-generated discourse surrounding the topic. This study was conducted to describe SM interactions about weight through a mixed methods analysis. Data were collected across 60 days through SM monitoring services, yielding 2.2 million posts. Data were cleaned and coded through Natural Language Processing (NLP) techniques, yielding popular themes and the most retweeted content. Qualitative analyses of selected posts add insight into the nature of the public dialogue and motivations for participation. Twitter represented the most common channel. Twitter and Facebook were dominated by derogatory and misogynist sentiment, pointing to weight stigmatization, whereas blogs and forums contained more nuanced comments. Other themes included humor, education, and positive sentiment countering weight-based stereotypes. This study documented weight-related attitudes and perceptions. This knowledge will inform public health/obesity prevention practice. |
X Demographics
The data shown below were collected from the profiles of 28 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 10 | 36% |
| Netherlands | 2 | 7% |
| United Kingdom | 2 | 7% |
| Argentina | 1 | 4% |
| Belgium | 1 | 4% |
| Japan | 1 | 4% |
| Colombia | 1 | 4% |
| Ireland | 1 | 4% |
| Canada | 1 | 4% |
| Other | 1 | 4% |
| Unknown | 7 | 25% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 19 | 68% |
| Practitioners (doctors, other healthcare professionals) | 5 | 18% |
| Scientists | 4 | 14% |
Mendeley readers
The data shown below were compiled from readership statistics for 296 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Australia | 2 | <1% |
| Bahrain | 1 | <1% |
| United Kingdom | 1 | <1% |
| Canada | 1 | <1% |
| Spain | 1 | <1% |
| United States | 1 | <1% |
| Unknown | 289 | 98% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 46 | 16% |
| Student > Ph. D. Student | 33 | 11% |
| Student > Bachelor | 32 | 11% |
| Student > Doctoral Student | 26 | 9% |
| Researcher | 19 | 6% |
| Other | 61 | 21% |
| Unknown | 79 | 27% |
| Readers by discipline | Count | As % |
|---|---|---|
| Psychology | 52 | 18% |
| Social Sciences | 42 | 14% |
| Medicine and Dentistry | 25 | 8% |
| Computer Science | 16 | 5% |
| Nursing and Health Professions | 15 | 5% |
| Other | 51 | 17% |
| Unknown | 95 | 32% |
Attention Score in Context
This research output has an Altmetric Attention Score of 66. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 24 December 2023.
All research outputs
#657,867
of 25,758,211 outputs
Outputs from Translational Behavioral Medicine
#25
of 1,093 outputs
Outputs of similar age
#5,865
of 236,488 outputs
Outputs of similar age from Translational Behavioral Medicine
#1
of 9 outputs
Altmetric has tracked 25,758,211 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 97th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,093 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.0. This one has done particularly well, scoring higher than 97% of its peers.
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We're also able to compare this research output to 9 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them