Abstract
BACKGROUND: With the extensive development of social media and the rapid dissemination of online information, online public opinion has become an important medium for shaping the public’s perception of mental health. However, the fragmented, emotional and polarized nature of online information can easily lead to a deviation in the public’s perception of mental health issues such as schizophrenia. Most of the existing research focuses on the qualitative description of public opinion trends or individual case analyses of mental health cognition, lacking data-driven quantitative research. Therefore, this study aims to explore the impact of online public opinion on the public’s mental health cognition through data analysis methods. METHODS: The research adopted a hybrid research method combining quantitative data analysis with content analysis for the experiment. Firstly, a web crawler tool was used to collect over 120 000 pieces of online text data related to schizophrenia, mental health, etc. from mainstream social media platforms such as Weibo, Zhihu, and Douban. The data was preprocessed through steps such as deduplication, word segmentation, and stop word removal. Then, natural language processing technology is used to extract the key features of online public opinion, including emotional tendency, topic distribution and information dissemination intensity. Subsequently, a questionnaire survey was conducted among 800 respondents of different ages, educational backgrounds and regions to test their cognitive levels and attitude tendencies towards schizophrenia. Finally, through correlation analysis and regression analysis, the association between the characteristics of online public opinion and the indicators of public cognition and attitude was explored. RESULTS: Data analysis results show that in online public opinions related to schizophrenia, negative emotions account for 62.18%, while positive emotions and neutral emotions only make up 18.34% and 19.48% respectively. Moreover, the topics of public opinion mainly focus on symptom description (35.50%) and social discrimination (28.93%). However, the proportion of topics related to scientific treatment (20.31%) and policy support (15.26%) is relatively low. Correlation analysis indicated that the intensity of negative public opinion dissemination was significantly negatively correlated with the public’s correct awareness rate of schizophrenia (p<.01), and significantly positively correlated with the degree of public discriminatory attitude (p<.01). The results of the regression analysis show that the proportion of negative emotions and topics related to social discrimination in public opinion is the main factor influencing the public’s cognitive bias towards schizophrenia. Furthermore, the research found that respondents who frequently interact with social media have a 32.62% lower correct awareness rate of schizophrenia and a 25.71% higher tendency towards discrimination than those who have less exposure. DISCUSSION: The research results show that online public opinion has a significant impact on the public’s cognition and attitude towards schizophrenia. Among them, the negative tendency of public opinion and the imbalance of topic distribution are important factors leading to public cognitive bias and discriminatory behavior. The research results provide empirical evidence for understanding the relationship between online information dissemination and mental health cognition, and have significant practical significance for promoting the supervision of online public opinion and reducing the social stigmatization of mental illness.