利用社交媒体数据研究COVID-19疫情 / Leveraging Social Media Data for COVID-19 Studies
1️⃣ 一句话总结
本文系统总结了在COVID-19疫情期间,如何利用社交媒体平台上用户发布的内容(如语言、图像和情绪表达)来提取有价值的信息,并介绍了用于分析这些数据的机器学习、自然语言处理等技术方法,旨在帮助公众、医生和社会更有效地获取可靠信息并应对疫情。
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.
利用社交媒体数据研究COVID-19疫情 / Leveraging Social Media Data for COVID-19 Studies
本文系统总结了在COVID-19疫情期间,如何利用社交媒体平台上用户发布的内容(如语言、图像和情绪表达)来提取有价值的信息,并介绍了用于分析这些数据的机器学习、自然语言处理等技术方法,旨在帮助公众、医生和社会更有效地获取可靠信息并应对疫情。
源自 arXiv: 2606.10459