Monitoring and understanding social emotions

By Gong Weigang, Zhuang Yonggai / 02-26-2024 / Chinese Social Sciences Today

Emojis are used to express emotions on social media. Photo: TUCHONG

Social emotions serve as a barometer for assessing the functioning of the social system. Significant public events often trigger drastic shifts in social emotions. For instance, during times of war, the public may experience feelings of helplessness and despair. Enhancing social governance capabilities becomes imperative in response to these changes. Comprehensive data and advanced methodologies lay the foundation for monitoring and understanding social emotions, which can be improved by adopting appropriate perspectives and approaches.

Data and methodology

In social science research, due to the lack of comprehensive data, social systems, which are vast and intricate, are typically analyzed based on a subset of elements. However, in the era of big data, the wide range of internet-based information offers insights into the activities of a majority of society. For example, the widespread use of platforms like WeChat in China provides valuable data on user activities and the emotional information they leave behind, reflecting the circumstances of the population.

Various machine learning methods and natural language processing algorithms serve as excellent tools for analyzing non-traditionally structured data, such as internet big data. In particular, large language models greatly facilitate semantic understanding and sentiment analysis of text.

Perspective and approach

Several key perspectives contribute to the understanding of social emotions in the era of social transformation. Firstly, the structural narrative perspective of sociology should be flexibly adopted. Structural narrative helps analyze the influence of structural characteristics on social emotions. Conversely, analysis of social emotions can reveal the structural characteristics of society.

To illustrate, research by the author shows a close correlation between social structure and anxiety, resentment, and similar emotions. Anxiety, for instance, is particularly prevalent among certain groups such as entrepreneurs. The distribution of social emotions is closely related to the life circumstances and pressures faced by different groups in times of social transformation.

Secondly, it is important to focus on significant public events. During relatively stable periods, public emotional expression tends to be limited, making it challenging to identify important patterns. On the contrary, significant public events usually activate various latent social emotions, which is crucial to grasping public opinion in the process of social governance.

The occurrence and evolution of significant public events often result in the concentration of public attention and the eruption of social emotions. When various stances, attitudes, and viewpoints compete for attention, latent regularities and structural characteristics of the social system can be observed. In contrast, it is difficult to uncover underlying currents during calm periods when the social system’s elements are dispersed and lack aggregated interaction.

Meanwhile, diverse viewpoints and forces interact in a variety of ways as significant public events unfold, which could become an outlet for pent-up emotions. Without prompt social control and guidance, this can lead to secondary disasters, threatening social stability.

The author’s analysis of social media big data from 2020 to 2022 reveals that panic, anxiety, and depression were the prevailing social emotions during this period, particularly in the first half of 2020. Subsequent observations indicate a decrease in the intensity of these emotional fluctuations, albeit to a lesser extent. Social psychology recognizes distinct phases of crisis, characterized by panic, anxiety, and depression, followed by a return to a state of calmness. These emotional transitions are closely related to government actions and measures taken at the societal level.

Thirdly, it is necessary to closely examine the impact of great power competition and economic conditions on social emotions. While established research on social mentality primarily concentrates on the context of social transformation, great power competition has emerged as an essential determinant of social emotions, particularly as the world is experiencing accelerating and unprecedented changes. In the internet era, social mentality and social cognition constitute important fields of great power competition. The integration of cognitive interference and manipulation with competition in physical domains has considerable impact on social mentality.

Research has demonstrated that the impact of economic conditions on social mentality cannot be ignored. Dynamic monitoring and early warning of social emotions aimed at maintaining social stability are critical to social governance during periods of economic downturn, which often witness the intensification of social conflicts and an increase in social ills.

Lastly, the analysis of social emotions needs to consider the social context of digital transformation. The internet has ushered human society into a highly emotional era, with frequent outbursts of frenzy and large-scale contagion of anxiety on social media platforms. This era presents a unique landscape that has not been witnessed in social science research before.

Big data consolidates the trickle of information in social life into an ocean of data. In such an era, a fundamental issue for sociology is to leverage the robust information processing capabilities of cloud computing to analyze massive amounts of internet data, thereby gaining insights into the evolving patterns of social emotions.

Gong Weigang (associate professor) is from the School of Sociology at Wuhan University. Zhuang Yonggai is from the School of Journalism and Communication at Wuhan University.