Changes in Public Sentiment under the Background of Major Emergencies—Taking the Shanghai Epidemic as an Example
Abstract
:1. Introduction
2. Deep Learning in the Emotion Domain
3. Methodology
3.1. Study Design
3.2. Data Sources
3.2.1. Acquisition of Weibo Comment Data
3.2.2. Data Preprocessing
3.3. Methods
3.3.1. Lexical Analysis of Chinese (LAC)
3.3.2. Keyword Weight Calculation
3.3.3. ERNIE Pre-Training Model
3.3.4. Estimating Transfer Entropy via Copula Entropy
3.3.5. Semantic Network Analysis
4. Results
4.1. Data Analysis
4.2. Temporal Changes in Emotion Classification
4.3. Analysis of Causality
4.4. Social Network Analysis in Different Emotional Periods
4.4.1. Emotional Fermentation Period
4.4.2. Emotional Climax Period
4.4.3. Emotional Chaos Period
5. Discussion
5.1. Significance and Recommendations
- (1)
- The emotional fermentation period is generally at the early stage of the epidemic, where the impact of the epidemic is at its lowest and is not yet wide-ranging. At this time, prevention and control measures should be taken in a timely manner to ensure two-way communication and exchanges with the masses. The active publication of anti-epidemic events will help facilitate the public’s positive emotions to combat the epidemic and ensure the effective implementation of anti-epidemic policies. The public needs to lead by example, provide help and care to others, maintain a good attitude, and actively pay attention to the national government’s epidemic prevention policies and dynamic changes during the epidemic, but refrain from excessive remarks.
- (2)
- When the public mood reaches its climax, it signifies that the epidemic has begun to affect the normal lives of most local residents and has even begun to permeate to other provinces and cities. The focus should be on improving emergency medical treatment capabilities and material supply and demand matching capabilities, as well as the effective stabilization and standardization of markets. The media should publicize as much as possible, local anti-epidemic heroic deeds and the anti-epidemic assistance of other provinces and municipalities to reduce the focus on daily living issues and negative emotions caused by the epidemic. In addition, since most of the attention of the public is on the epidemic itself, the most obvious fundamental action to regulate the negative emotions of the public is to effectively control the spread of the epidemic.
- (3)
- When public sentiment reaches a chaotic stage, it signifies that the spread of the epidemic has exceeded most of the public’s expectations, and they gradually begin to reduce their attention on the epidemic and its corresponding events. The erroneous notion, “do not take measures and let the epidemic continue to develop,” gradually emerges in the hearts of the public. To guide citizens more effectively, it is necessary to strengthen epidemic prevention measures, reduce the number of new cases every day, and provide the public with actual data showing progress.
5.2. Limitations and Scope for Future Study
6. Conclusions
- During a public health emergency, public sentiment can be greatly affected. During the Shanghai outbreak, negative emotions dominated known emotional responses. In addition, among the negative emotions, sadness accounted for 16.96% and anger accounted for 25.68%. Therefore, anger was the primary negative emotion expressed;
- Public sentiment during the epidemic was affected by factors such as public behavior, government behavior, and the severity of the epidemic. In the pre-period, public behavior and government behavior dominated public sentiment. Later, the severity of the epidemic gradually dominated public sentiment;
- From the perspective of time series changes, the changes in public sentiment during the Shanghai epidemic can be divided into three periods: the emotional fermentation period, the emotional climax period, and the emotional chaos period. Through social network analysis, it was found that the epidemic has always been the core of public attention. However, as the emotional period changed, the positive sentiment of the public began to fade. Instead, the public became concerned about their own safety and security.
- The impact of the epidemic on the negative emotions of the public was greater than on the positive emotions, indicating that the public is more likely to experience negative emotions during major adverse health events. In addition, a causal relationship between positive emotions and negative emotions was detected, indicating that positive emotions have a certain inhibitory effect on negative emotions.
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Comment Date | Reviewer Nickname | Title Link | Comment |
---|---|---|---|
10 March 2022 | Goose egg sister is not softhearted | https://weibo.com/u/7338779976 (accessed on 20 April 2022) | Chengdu is almost free of the epidemic. We’re down to a low-risk area. Come on. |
3 April 2022 | Missing little kids | https://weibo.com/u/2036291735 (accessed on 20 April 2022) | Love your city and cooperate with all anti-epidemic arrangements. Fighting the epidemic together |
5 April 2022 | Cheese Pig Zyra | https://weibo.com/u/2608700454 (accessed on 20 April 2022) | I feel the management gap in the region. Baoshan has not distributed materials and parts of Pudong. |
Key Words | Frequency | tf | idf | tfidf | Key Words | Frequency | tf | idf | tfidf |
---|---|---|---|---|---|---|---|---|---|
Shanghai | 19636 | 135.42 | 0.79 | 106.86 | Thanks | 1875 | 12.93 | 1.74 | 22.54 |
Epidemic | 7781 | 53.66 | 1.15 | 61.97 | Ask for help | 1750 | 12.07 | 1.85 | 22.31 |
Come on | 5027 | 34.67 | 1.36 | 47.30 | 1711 | 11.80 | 1.79 | 21.17 | |
Community | 2989 | 20.61 | 1.58 | 32.60 | Positive | 1502 | 10.36 | 1.89 | 19.54 |
Nucleic acid | 2941 | 20.28 | 1.60 | 32.44 | Government | 1530 | 10.55 | 1.81 | 19.14 |
Isolation | 2829 | 19.51 | 1.62 | 31.58 | Epidemic prevention | 1455 | 10.03 | 1.87 | 18.79 |
Sad | 2594 | 17.89 | 1.58 | 28.26 | Shenzhen | 1340 | 9.24 | 1.92 | 17.76 |
Anti-epidemic | 2012 | 13.88 | 1.78 | 24.65 | Safety | 1380 | 9.52 | 1.84 | 17.50 |
Materials | 2083 | 14.37 | 1.71 | 24.55 | Bitter | 1333 | 9.19 | 1.87 | 17.18 |
Shanghai residents | 1930 | 13.31 | 1.76 | 23.49 | Hospital | 1259 | 8.68 | 1.96 | 17.03 |
Emotion | Example |
---|---|
Gratitude | It’s hard work, the angels on the front line are hard work. Pay attention to protection and return safely. You guys are the best! |
Confidence | I believe that the epidemic situation in Shanghai will soon see the light of day. |
Sad | We haven’t started school in Shenzhen yet, sad! When the epidemic is over, it is estimated that another half semester will have passed. I am really heartbroken! |
Anger | Are Shanghainese not Chinese? Half of the flight goes to Shanghai, have you ever thought that the life of Shanghai people is also life? |
No emotion | The courier guys in Hangzhou should all be quarantined! Does it feel like the courier guys across the country have been quarantined? |
Emotion Category | Accuracy | Recall | F1 |
---|---|---|---|
Gratitude | 0.9694 | 0.9596 | 0.9645 |
Confidence | 0.9714 | 0.9533 | 0.9623 |
Sad | 0.9184 | 0.9091 | 0.9137 |
Anger | 0.7593 | 0.8454 | 0.8000 |
No emotion | 0.8132 | 0.7551 | 0.7831 |
Emotion Category | Quantity | Proportion | ||
---|---|---|---|---|
Positive emotions | Gratitude | 10,858 | 12.14% | 19.81% |
Confidence | 6864 | 7.67% | ||
Negative emotions | Sad | 15,174 | 16.96% | 42.64% |
Anger | 22,975 | 25.68% | ||
No emotion | 33,597 | 37.55% | 37.55% |
Date | Positive Emotions | Negative Emotions | Daily New Cases | Date | Positive Emotions | Negative Emotions | Daily New Cases |
---|---|---|---|---|---|---|---|
3.10 | 10 | 2 | 75 | 3.25 | 21 | 221 | 2269 |
3.11 | 210 | 219 | 83 | 3.26 | 190 | 226 | 2676 |
3.12 | −85 | −25 | 65 | 3.27 | −191 | 379 | 3500 |
3.13 | 101 | 81 | 169 | 3.28 | −75 | −376 | 4477 |
3.14 | 340 | 240 | 139 | 3.29 | −24 | 12 | 5982 |
3.15 | −210 | 146 | 202 | 3.30 | 307 | 608 | 5653 |
3.16 | 198 | −325 | 158 | 3.31 | 188 | 476 | 4502 |
3.17 | −248 | −166 | 260 | 4.1 | −301 | −603 | 6311 |
3.18 | −40 | 19 | 374 | 4.2 | 373 | 1543 | 8226 |
3.19 | −107 | 21 | 509 | 4.3 | 295 | 299 | 9006 |
3.20 | 383 | 137 | 758 | 4.4 | 482 | −117 | 13,354 |
3.21 | 17 | −109 | 896 | 4.5 | −385 | 412 | 17,077 |
3.22 | −149 | 24 | 981 | 4.6 | −19 | −161 | 19,982 |
3.23 | −216 | 112 | 983 | 4.7 | −79 | −199 | 21,222 |
3.24 | 167 | 26 | 1609 | 4.8 | 20 | 527 | 23,624 |
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Zhang, B.; Lin, J.; Luo, M.; Zeng, C.; Feng, J.; Zhou, M.; Deng, F. Changes in Public Sentiment under the Background of Major Emergencies—Taking the Shanghai Epidemic as an Example. Int. J. Environ. Res. Public Health 2022, 19, 12594. https://doi.org/10.3390/ijerph191912594
Zhang B, Lin J, Luo M, Zeng C, Feng J, Zhou M, Deng F. Changes in Public Sentiment under the Background of Major Emergencies—Taking the Shanghai Epidemic as an Example. International Journal of Environmental Research and Public Health. 2022; 19(19):12594. https://doi.org/10.3390/ijerph191912594
Chicago/Turabian StyleZhang, Bowen, Jinping Lin, Man Luo, Changxian Zeng, Jiajia Feng, Meiqi Zhou, and Fuying Deng. 2022. "Changes in Public Sentiment under the Background of Major Emergencies—Taking the Shanghai Epidemic as an Example" International Journal of Environmental Research and Public Health 19, no. 19: 12594. https://doi.org/10.3390/ijerph191912594