RESEARCH ON THE EXPRESSION OF PUBLIC EMOTION AND BEHAVIOR IN MICROBLOG PUBLIC OPINION
Bibliographic record
Abstract
Abstract Background Compared with the public opinion in the era of traditional media, microblog public opinion shows different characteristics, among which the strong expression of public emotion and behavior is important and has practical impact. The important factor that microblog public opinion has a significant influence is that microblog directly reflects the public mood. Unlike traditional mass media, microblog is a direct point-to-point communication, and the influence comes from the nested microblog relationship. This exponential communication influence enables the public mood to spread to every corner of the world in a short time. In an article entitled “Public opinion formed by anger”, the author quoted the research results of Beijing University of Aeronautics and Astronautics as saying that anger spreads faster on microblog than any emotion. The article also points out that microblogging has become the most convenient channel for Chinese people to participate in social discussion and express concern. The anger expressed in social contacts has promoted the dissemination of relevant news and accelerated the formation of public opinions and collective action. In fact, in many social fields in china, the trend of emotion in microblog has become an important aspect of public opinion prediction, even in crime prevention and economic development. Unfortunately, while people are keen to feel and use the emotional factors in microblog, they have not made a rational exploration of it. Based on the above background, this study intends to start from four aspects: First, why there are obvious emotional characteristics in microblog public opinion compared with traditional mass media; second, what kind of emotions exist in microblog public opinion and what is the relationship with the current social reality; third, how to express the emotions in microblog public opinion and how to present them; fourth, what are the social effects of emotional behavior in microblog public opinion and how to deal with the negative social effects. Subjects and Methods This paper takes psychological research as the main orientation, and pays attention to the public emotional factors in microblog public opinion. The main research methods are as follows: 1 literature method, through the collection and analysis of public opinion research, microblog research and public sentiment research, this paper selects the content related to this research and analyzes, arranges, synthesizes and uses it. Based on the above research, this paper puts forward a new dimension of public opinion research, and tries to innovate in research content, research perspective and research methods. 2. Case analysis method: On the basis of combing the context of the event, conduct text analysis and data statistics, register microblog through real name and interact with other users, and observe and collect relevant materials in the process of interaction. Questionnaire survey method in order to catch a glimpse of the leopard. 3. Questionnaire survey, using scl-90 questionnaire, 208 microblog creators were selected to investigate and analyze the emotional and behavioral factors. Ten factors include somatization, anxiety, compulsion and so on. Results The research found that with the continuous development of the internet, public emotional behavior will have an important impact on microblog public opinion. There are two directions: One is the top-down impact, the other is the bottom-up impact; it is mainly manifested in two typical ways: Social mobilization and emotional social struggle in microblog public opinion. The main expressions of their emotional behavior are: Weakness, anger, sadness and anger, etc. On the basis of combing the collective behavior and emotional struggle, the research finds that the communication framework of emotional behavior mainly includes the communication paths of discourse co meaning, identity co meaning and emotional co meaning; functional analysis includes target function, attribution function and ideographic function. From the tendency of public sentiment, microblog public opinion shows criticism, populism, nationalism, pragmatism, patriotism and justice. The social expression of public sentiment in microblog public opinion includes the spiral phenomenon of silence, butterfly effect, herd effect, resentment and so on. From the perspective of psychology, the public emotions in microblog public opinion are expressed as fear, anxiety, anger and sadness, while in terms of expression, the public express their feelings through direct expression, folk language and other ways. Conclusion The social effects of negative emotions in microblog public opinion have their own paths and standards of research and judgment, and we need to deal with the social effects of negative emotions. In the process of response, we should follow the principles of first time, multi opinion space construction, affinity and self-centered, strengthen the construction of service-oriented government, establish a three-dimensional communication pattern, and establish monitoring, early warning and feedback mechanisms. Acknowledgements This work was supported by the National Natural Science Foundation of China [grant numbers 71704085, 71874088] and Postgraduate Research & Practice Innovation Program of Jiangsu Province [Grant number KYCX21_0832].
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".