Research on the Characteristics of Internet Public Opinion and Public Sentiment after the Sichuan Earthquake Based on the Perspective of Weibo
In this paper, based on Sina Weibo data, a natural language processing (NLP) analysis method was used to analyze the temporal and spatial sequence characteristics of people’s attention and the characteristics of text content with the help of microblogs posted by people within 6 days after the 2022 L...
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-01-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/13/3/1335 |
| _version_ | 1797625225283633152 |
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| author | Weiming He Qinglu Yuan Nan Li |
| author_facet | Weiming He Qinglu Yuan Nan Li |
| author_sort | Weiming He |
| collection | DOAJ |
| description | In this paper, based on Sina Weibo data, a natural language processing (NLP) analysis method was used to analyze the temporal and spatial sequence characteristics of people’s attention and the characteristics of text content with the help of microblogs posted by people within 6 days after the 2022 Lushan M6.1, Maerkang M5.8 and Luding M6.8 earthquakes. Moreover, the same analysis method was used on the content of comments on microblogs posted by official media outlets within 6 days after the earthquakes to analyze the changes in people’s sentiments and the differences in the sentiments in various regions, and the influencing factors were also analyzed. The results of this research show the following: In terms of the spatial and temporal distributions, people’s attention was affected by the earthquakes themselves and their social impacts, and the first 2 h was often a period of an outbreak of attention, with the publishing areas mainly concentrated in Sichuan and Guangdong. In terms of people’s sentiments, the overall microblogging sentiment of the three earthquakes was positive, and the sentiment value of the people in Sichuan was generally low compared with that of the people in the other regions. Not only was the fluctuation in sentiment affected by the influence of the region, but it was also positively related to the sentiment of official microblogs. The results of this research provide reference for guiding people’s sentiments after earthquakes in the new media era. |
| first_indexed | 2024-03-11T09:53:33Z |
| format | Article |
| id | doaj.art-f31372091c4a4485ba8dac87222131ed |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-11T09:53:33Z |
| publishDate | 2023-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-f31372091c4a4485ba8dac87222131ed2023-11-16T16:03:59ZengMDPI AGApplied Sciences2076-34172023-01-01133133510.3390/app13031335Research on the Characteristics of Internet Public Opinion and Public Sentiment after the Sichuan Earthquake Based on the Perspective of WeiboWeiming He0Qinglu Yuan1Nan Li2School of Economic and Management, Institute of Disaster Prevention, Beijing 101601, ChinaSchool of Economic and Management, Institute of Disaster Prevention, Beijing 101601, ChinaSchool of Economic and Management, Institute of Disaster Prevention, Beijing 101601, ChinaIn this paper, based on Sina Weibo data, a natural language processing (NLP) analysis method was used to analyze the temporal and spatial sequence characteristics of people’s attention and the characteristics of text content with the help of microblogs posted by people within 6 days after the 2022 Lushan M6.1, Maerkang M5.8 and Luding M6.8 earthquakes. Moreover, the same analysis method was used on the content of comments on microblogs posted by official media outlets within 6 days after the earthquakes to analyze the changes in people’s sentiments and the differences in the sentiments in various regions, and the influencing factors were also analyzed. The results of this research show the following: In terms of the spatial and temporal distributions, people’s attention was affected by the earthquakes themselves and their social impacts, and the first 2 h was often a period of an outbreak of attention, with the publishing areas mainly concentrated in Sichuan and Guangdong. In terms of people’s sentiments, the overall microblogging sentiment of the three earthquakes was positive, and the sentiment value of the people in Sichuan was generally low compared with that of the people in the other regions. Not only was the fluctuation in sentiment affected by the influence of the region, but it was also positively related to the sentiment of official microblogs. The results of this research provide reference for guiding people’s sentiments after earthquakes in the new media era.https://www.mdpi.com/2076-3417/13/3/1335microblog dataSichuan earthquakepublic sentimentnatural language processing |
| spellingShingle | Weiming He Qinglu Yuan Nan Li Research on the Characteristics of Internet Public Opinion and Public Sentiment after the Sichuan Earthquake Based on the Perspective of Weibo Applied Sciences microblog data Sichuan earthquake public sentiment natural language processing |
| title | Research on the Characteristics of Internet Public Opinion and Public Sentiment after the Sichuan Earthquake Based on the Perspective of Weibo |
| title_full | Research on the Characteristics of Internet Public Opinion and Public Sentiment after the Sichuan Earthquake Based on the Perspective of Weibo |
| title_fullStr | Research on the Characteristics of Internet Public Opinion and Public Sentiment after the Sichuan Earthquake Based on the Perspective of Weibo |
| title_full_unstemmed | Research on the Characteristics of Internet Public Opinion and Public Sentiment after the Sichuan Earthquake Based on the Perspective of Weibo |
| title_short | Research on the Characteristics of Internet Public Opinion and Public Sentiment after the Sichuan Earthquake Based on the Perspective of Weibo |
| title_sort | research on the characteristics of internet public opinion and public sentiment after the sichuan earthquake based on the perspective of weibo |
| topic | microblog data Sichuan earthquake public sentiment natural language processing |
| url | https://www.mdpi.com/2076-3417/13/3/1335 |
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