Research shows that certain external factors can affect the mental health of many people in a community. Moreover, the importance of mental health has significantly increased in recent years due to the COVID-19 pandemic. Many people communicate and express their emotions through social media platforms, which provide researchers with opportunities to examine insights into their opinions and mental state. While social sensing studies using social media data have flourished in the last decade, many studies using social media data to detect and predict mental health status have focused on the individual level. In this study, we aim to generate a social sensing index for mental health to monitor emotional well-being, which is closely related to mental health, and to identify daily trends in negative emotions at the city level. We conduct sentiment analysis on Twitter data and compute entropy of the degree of sentiment change to develop the index. We observe sentiment trends fluctuate significantly in response to unusual events. It is found that the social sensing index for mental health reflects both city-wide and local events that trigger negative emotions, as well as areas where negative emotions persist. The study contributes to the growing body of research that uses social media data to examine mental health at a city-level. We focus on mental health at the city-level rather than individual, which provides a broader perspective on the mental health of a population. Social sensing index for mental health allows public health professionals to monitor and identify persistent negative sentiments and potential areas where mental health issues may emerge.
Social media data offer a rich resource for researchers interested in public health, labor economics, politics, social behaviors, and other topics. However, scale and anonymity mean that researchers often cannot directly get permission from users to collect and analyze their social media data. This article applies the basic ethical principle of respect for persons to consider individuals’ perceptions of acceptable uses of data. We compare individuals’ perceptions of acceptable uses of other types of sensitive data, such as health records and individual identifiers, with their perceptions of acceptable uses of social media data. Our survey of 1018 people shows that individuals think of their social media data as moderately sensitive and agree that it should be protected. Respondents are generally okay with researchers using their data in social research but prefer that researchers clearly articulate benefits and seek explicit consent before conducting research. We argue that researchers must ensure that their research provides social benefits worthy of individual risks and that they must address those risks throughout the research process.
more » « less- PAR ID:
- 10376570
- Publisher / Repository:
- Nature Publishing Group
- Date Published:
- Journal Name:
- Scientific Data
- Volume:
- 9
- Issue:
- 1
- ISSN:
- 2052-4463
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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