利用社交媒体数据洞察新冠疫情期间公众情绪与信息传播
Leveraging Social Media Data for COVID-19 Studies
- 分析用户发布的语言、视觉和情感特征，提取疫情相关行为模式
- 涵盖46亿用户的数据规模，揭示社交平台在疫情信息传播中的作用
- 适合公共卫生研究者与社会计算领域学者参考
如今，社交媒体已成为人们获取信息的主要渠道。尤其在2019冠状病毒病（COVID-19）疫情期间，社交媒体成为获取最新资讯的重要平台。由于其对注册用户免费开放，并支持内容发布、传播与互动，全球近46亿用户活跃于各类社交平台，由此产生的海量信息显著影响公众对疫情的认知与应对。合理利用社交媒体可成为传播可靠信息与提升公众意识的有效数字工具。本文详细探讨了疫情期间社交媒体的使用情况，分析用户发布内容中的语言、视觉与情感指标，分类总结了所用社交数据类型，介绍机器学习、特征工程、自然语言处理及调查方法的应用，并展望未来研究方向。
原文摘要 · Abstract (English)
Nowadays, social media networks have become widely preferred sources of information. Especially during the time of the Coronavirus disease 2019 COVID 19 pandemic, social media has been one of the most used platforms to get the latest news and information related to COVID 19. Social media are popular because they offer free access to their registered users and allow them to do posting, disseminate information, and respond to others postings. With almost 4.6 billion social media users worldwide, it is not surprising the significant amount of information shared through these platforms could affect how people perceive and cope with the pandemic that we are facing right now. With decent use, social media can be a beneficial digital tool to spread reliable news and public awareness for patients, clinicians, and society. Specifically, this chapter describes linguistic, visual, and emotional indicators expressed in user disclosures. Thus, in this chapter, the related studies of social media platforms usage during the COVID 19 pandemic are explored and discussed in detail. This chapter also categorizes social media data used, introduces different deployed machine learning, feature engineering, natural language processing, and survey methods, and outlines directions for future research.
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