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Large-Scale, Mixed-Methods Analyses to Understand Social Media-Mediated Health-Related Communications during an Epidemic
MPhil Thesis Defence Title: "Large-Scale, Mixed-Methods Analyses to Understand Social Media-Mediated Health-Related Communications during an Epidemic" By Mr. Wenjie YANG Abstract Social media has substantially reduced communication barriers between ordinary people, patients, and healthcare providers. This popular Internet application is increasingly being used for health-related communications, such as by individuals seeking health information or services and by public health agencies for health promotion. However, the recent outbreaks of health crises like COVID-19 have created significant challenges for online health-related interaction. During epidemics, when online spaces are often flooded with (mis)information, it can be difficult and inefficient for people to obtain and exchange information using social networking services that are not designed to mediate disaster communications. Despite this, it remains unclear how social media technologies can be better used or improved to facilitate health-related communications during emergencies. In order to fill this gap, this thesis examines two significant cases of health-related communications during COVID-19 pandemic on Chinese social media, including online help-seeking by COVID patients and the spread and debunking of health rumors. Specifically, we ask 1) how people use social media for health-related communications during an epidemic, and 2) what are the affordances and limitations of the current social media design for this purpose? We answer the questions by analyzing over 100M Weibo posts with mixed methods, such as natural language processing, statistical analysis, and content analysis. As an interdisciplinary study, this thesis adds empirical understanding to human behavior, provides design implications regarding social media design for human-computer interaction (HCI) communities, and sheds light on better practices for crisis management. Date: Wednesday, 8 June 2022 Time: 2:00pm - 4:00pm Zoom Meeting: https://hkust.zoom.us/j/97934980614?pwd=S2Exd21xeGRxTVArUDBMN2ZSUlkwQT09 Committee Members: Dr. Xiaojuan Ma (Supervisor) Dr. Yangqiu Song (Chairperson) Prof. Bo Li **** ALL are Welcome ****