Nutrition Information Post COVID-19: A twitter content analysis

IF 0.6 Q4 Health Professions
Shagun Tomar, Manisha Gupta, Madhu Rani, Hari Shankar Shyam, Nishtha Ujjawal
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引用次数: 0

Abstract

Realizing social media's importance, many doctors, nutritionists, health coaches and general users have registered on social media and actively share health information. Users may easily access and exchange health information. It benefits both users and practitioners. Qualitative data analysis is employed to study Twitter communication content to understand better the relationship between users’ interest in healthy eating. The research examined Twitter nutrition health information using hashtags. The frequency of hashtags was ranked. The content analysis quantifies social media healthy diet hashtags. Theme modification and word and phrase recurrence analysis to identify two primary themes and significant sentiments relating to Covid-19 and nutrition. Python and NLP are used to analyze and interpret the data to help acquire in-depth information.
营养信息发布COVID-19:推特内容分析
意识到社交媒体的重要性,许多医生、营养师、健康教练和普通用户都在社交媒体上注册,并积极分享健康信息。用户可以方便地访问和交换健康信息。它对用户和从业者都有好处。采用定性数据分析对Twitter传播内容进行研究,更好地了解用户对健康饮食的兴趣之间的关系。该研究使用标签检查了推特上的营养健康信息。对标签的使用频率进行了排名。内容分析量化了社交媒体健康饮食标签。主题修改和单词和短语重复分析,以确定与Covid-19和营养有关的两个主要主题和重要情绪。使用Python和NLP来分析和解释数据,以帮助获取深入的信息。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Asia Pacific Journal of Health Management
Asia Pacific Journal of Health Management HEALTH POLICY & SERVICES-
CiteScore
1.10
自引率
16.70%
发文量
51
审稿时长
9 weeks
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