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通过分析推特来识别与饮食失调症状相关的话题。

Analysis of Twitter to Identify Topics Related to Eating Disorder Symptoms.

作者信息

Zhou Sicheng, Bian Jiang, Zhao Yunpeng, Haynos Ann F, Rizvi Rubina, Zhang Rui

机构信息

Institute for Health Informatics, University of Minnesota, Minneapolis, MN, USA.

Department of Health Outcomes & Biomedical Informatics, University of Florida, Gainsville, FL, USA.

出版信息

Proc (IEEE Int Conf Healthc Inform). 2019 Jun;2019. doi: 10.1109/ichi.2019.8904863. Epub 2019 Nov 21.


DOI:10.1109/ichi.2019.8904863
PMID:32030368
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7003291/
Abstract

Eating disorders (EDs) are serious mental illnesses associated with physical and psychiatric problems, and premature death. Examining social media communication about ED symptoms may provide insight into how to prevent and treat these disorders. This study is to explore topics on Twitter related to EDs. We applied the Correlation Explanation (CorEx) topic model on 18,288 ED-related tweets and identified 20 topics, which were further grouped into 8 categories. The top two topic categories are body image and ED consequences. We manually evaluated the relevance of tweets to their assigned topics and average accuracy is 77.86%. Our findings are consistent with another study using content analysis, and we identified additional topics, such as ED consequences, pornography, and treatment and education from these tweets.

摘要

饮食失调是与身体和精神问题以及过早死亡相关的严重精神疾病。研究社交媒体上有关饮食失调症状的交流,可能会为如何预防和治疗这些疾病提供见解。本研究旨在探索推特上与饮食失调相关的话题。我们将相关解释(CorEx)主题模型应用于18288条与饮食失调相关的推文,并识别出20个主题,这些主题进一步被归为8类。前两个主题类别是身体形象和饮食失调的后果。我们人工评估了推文与所分配主题的相关性,平均准确率为77.86%。我们的研究结果与另一项使用内容分析的研究一致,并且我们从这些推文中识别出了其他主题,如饮食失调的后果、色情内容以及治疗和教育。

相似文献

[1]
Analysis of Twitter to Identify Topics Related to Eating Disorder Symptoms.

Proc (IEEE Int Conf Healthc Inform). 2019-6

[2]
Exploring Eating Disorder Topics on Twitter: Machine Learning Approach.

JMIR Med Inform. 2020-10-30

[3]
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[4]
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[5]
"I just want to be skinny.": A content analysis of tweets expressing eating disorder symptoms.

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[6]
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[7]
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[8]
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[9]
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[10]
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引用本文的文献

[1]
Characterizing the Discourse of Popular Diets to Describe Information Dispersal and Identify Leading Voices, Interaction, and Themes of Mental Health: Social Network Analysis.

JMIR Infodemiology. 2023-5-5

[2]
Potential benefits and limitations of machine learning in the field of eating disorders: current research and future directions.

J Eat Disord. 2022-5-8

[3]
Examining the Pro-Eating Disorders Community on Twitter Via the Hashtag #proana: Statistical Modeling Approach.

JMIR Ment Health. 2021-7-9

[4]
Exploring Eating Disorder Topics on Twitter: Machine Learning Approach.

JMIR Med Inform. 2020-10-30

本文引用的文献

[1]
Analyzing Social Media Data to Understand Consumer Information Needs on Dietary Supplements.

Stud Health Technol Inform. 2019-8-21

[2]
Exploring temporal suicidal behavior patterns on social media: Insight from Twitter analytics.

Health Informatics J. 2020-6

[3]
Mechanisms of behavior change in motivational interviewing: do we understand how MI works?

Curr Opin Psychol. 2018-12-18

[4]
"I just want to be skinny.": A content analysis of tweets expressing eating disorder symptoms.

PLoS One. 2019-1-16

[5]
Prevalence and Correlates of DSM-5-Defined Eating Disorders in a Nationally Representative Sample of U.S. Adults.

Biol Psychiatry. 2018-4-17

[6]
Self-Criticism as a Transdiagnostic Process in Nonsuicidal Self-Injury and Disordered Eating: Systematic Review and Meta-Analysis.

Suicide Life Threat Behav. 2018-3-5

[7]
Facebook usage among those who have received treatment for an eating disorder in a group setting.

Int J Eat Disord. 2016-8

[8]
#Proana: Pro-Eating Disorder Socialization on Twitter.

J Adolesc Health. 2016-6

[9]
The enigmatic persistence of anorexia nervosa.

Am J Psychiatry. 2013-5

[10]
Mortality rates in patients with anorexia nervosa and other eating disorders. A meta-analysis of 36 studies.

Arch Gen Psychiatry. 2011-7

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