RESUMEN
The outbreak of the COVID-19 pandemic has triggered citizen panic and social crises worldwide. The Chinese government was the first to implement strict prevention and control policies. However, in December 2022, the Chinese government suddenly changed its prevention and control policies and completely opened up. This led to a large-scale infection of the epidemic in a short period of time, which will cause unknown social impacts. This study collected 500+ epidemic-related hotspots and 200,000+ data from November 1, 2022, to March 1, 2023. Using a sentiment classification method based on pre-trained neural network models, we conducted inductive analysis and a summary of high-frequency words of various emotions. This study focuses on the inflection point of the emotional evolution of social media users and the evolution of "hot topic searches" events and emotional behavioral factors after the sudden open policy. Our research results show that, first of all, the positive emotions of social media users are divided into 4 inflection points and 5 time periods, and the negative emotions are divided into 3 inflection points and 4 time periods. Behavioral factors are different at each stage of each emotion. And the evolution patterns of positive emotions and negative emotions are also different. Secondly, the evolution of behavioral elements deserves more attention. Continue to pay attention: The treatment of diseases, the recovery of personal health, the promotion of festive atmosphere, and the reduction of publicity on the harm of "new crown sequelae and second infections" are the behavioral concerns that affect users' emotional changes. Finally, it is necessary to change the "hot topic searches" event by guiding the user's behavioral focus to control the inflection point of the user's emotion. This study helps governments and institutions understand the dynamic impact of epidemic policy changes on social media users, thereby promoting policy formulation and better coping with social crises.
Asunto(s)
COVID-19 , Medios de Comunicación Sociales , Humanos , COVID-19/epidemiología , COVID-19/psicología , Pandemias , Estudios Longitudinales , Emociones , China/epidemiologíaRESUMEN
Introduction: Since the outbreak of the COVID-19 pandemic, the Chinese government has implemented a series of strict prevention and control policies to prevent the spread of the virus. Recently, the Chinese government suddenly changed its approach and lifted all prevention and control measures. This sudden change in policy is expected to lead to a widespread outbreak of COVID-19 in China, and the public and local governments are not adequately prepared for the unknown impact on society. The change in the "emergency" prevention and control policy provides a unique research perspective for this study. Methods: The purpose of this study is to analyze the public's attitudes and emotional responses to COVID-19 under the sudden opening policy, identify the key factors that contribute to these attitudes and emotions, and propose solutions. In response to this sudden situation, we conducted data mining on topics and discussions related to the opening of the epidemic on Sina Weibo, collecting 125,686 interactive comments. We used artificial intelligence technology to analyze the attitudes and emotions reflected in each data point, identify the key factors that contribute to these attitudes and emotions, explore the underlying reasons, and find corresponding solutions. Results: The results of the study show that in the face of the sudden release of the epidemic, the public mostly exhibited negative emotions and behaviors, with many people experiencing anxiety and panic. However, the gradual resumption of daily life and work has also led some people to exhibit positive attitudes. Conclusion: The significance of this study is to help the government and institutions understand the impact of policy implementation on users, and to enable them to adjust policies in a timely manner to respond to potential social risks. The government, emergency departments, and the public can all prepare for similar situations based on the conclusions of this study.
Asunto(s)
COVID-19 , Medios de Comunicación Sociales , Humanos , Inteligencia Artificial , COVID-19/prevención & control , Emociones , Gobierno Local , Pandemias/prevención & control , Políticas , Procesamiento de Lenguaje NaturalRESUMEN
OBJECTIVE: In this rapidly digitizing world, it is becoming ever more important to understand people's online behaviors in both scientific and consumer research settings. The current work tests the feasibility of inferring personality traits from mouse movement patterns as a cost-effective means of measuring individual characteristics. METHOD: Mouse movement features (i.e., pauses, fixations, speed, and clicks) were collected while participants (N = 791) completed an online image choice task. We compare the results of standard univariate and three forms of multivariate partial least squares (PLS) analyses predicting Big Five traits from mouse movements. We also examine whether mouse movements can predict a proposed measure of task attentiveness (atypical responding), and how these might be related to personality traits. RESULTS: Each of the PLS analyses showed significant associations between a linear combination of personality traits (high Conscientiousness, Agreeableness, Openness, and low Neuroticism) and several mouse movements associated with slower, more deliberate responding (less unnecessary clicks and more fixations). Additionally, several click-related mouse features were associated with atypical responding on the task. CONCLUSIONS: As the image choice task itself is not intended to assess personality in any way, our results validate the feasibility of using mouse movements to infer internal traits across experimental contexts.