Understanding Discussions of Health Issues on Twitter: A Visual Analytic Study.

Online journal of public health informatics Pub Date : 2020-05-16 eCollection Date: 2020-01-01 DOI:10.5210/ojphi.v12i1.10321
Oluwakemi Ola, Kamran Sedig
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引用次数: 4

Abstract

Social media allows for the exploration of online discussions of health issues outside of traditional health spaces. Twitter is one of the largest social media platforms that allows users to post short comments (i.e., tweets). The unrestricted access to opinions and a large user base makes Twitter a major source for collection and quick dissemination of some health information. Health organizations, individuals, news organizations, businesses, and a host of other entities discuss health issues on Twitter. However, the enormous number of tweets presents challenges to those who seek to improve their knowledge of health issues. For instance, it is difficult to understand the overall sentiment on a health issue or the central message of the discourse. For Twitter to be an effective tool for health promotion, stakeholders need to be able to understand, analyze, and appraise health information and discussions on this platform. The purpose of this paper is to examine how a visual analytic study can provide insight into a variety of health issues on Twitter. Visual analytics enhances the understanding of data by combining computational models with interactive visualizations. Our study demonstrates how machine learning techniques and visualizations can be used to analyze and understand discussions of health issues on Twitter. In this paper, we report on the process of data collection, analysis of data, and representation of results. We present our findings and discuss the implications of this work to support the use of Twitter for health promotion.

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理解Twitter上健康问题的讨论:一项视觉分析研究。
社交媒体允许在传统卫生空间之外探索在线讨论卫生问题。Twitter是最大的社交媒体平台之一,允许用户发布简短的评论(即推文)。不受限制地获取意见和庞大的用户群使Twitter成为收集和快速传播某些健康信息的主要来源。卫生组织、个人、新闻机构、企业和许多其他实体在Twitter上讨论健康问题。然而,大量的推文给那些寻求提高健康问题知识的人带来了挑战。例如,很难理解对健康问题的总体看法或话语的中心信息。为了使Twitter成为促进健康的有效工具,利益相关者需要能够理解、分析和评估这个平台上的健康信息和讨论。本文的目的是研究视觉分析研究如何为Twitter上的各种健康问题提供见解。可视化分析通过将计算模型与交互式可视化相结合,增强了对数据的理解。我们的研究展示了如何使用机器学习技术和可视化来分析和理解Twitter上关于健康问题的讨论。在本文中,我们报告了数据收集,数据分析和结果表示的过程。我们提出了我们的发现,并讨论了这项工作的意义,以支持使用Twitter促进健康。
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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