| Id |
Subject |
Object |
Predicate |
Lexical cue |
| T1 |
0-51 |
Sentence |
denotes |
Social media concerns during the COVID-19 Pandemic: |
| T2 |
52-97 |
Sentence |
denotes |
An analysis of Sina Weibo Microblogging data. |
| T3 |
98-109 |
Sentence |
denotes |
BACKGROUND: |
| T4 |
110-219 |
Sentence |
denotes |
The COVID-19 pandemic has created a global health crisis, affecting economies and societies around the world. |
| T5 |
220-377 |
Sentence |
denotes |
During times of uncertainty and unexpected change, citizens have turned to social media as a mediating tool for communicating primary sources of information. |
| T6 |
378-645 |
Sentence |
denotes |
Platforms, such as Twitter and Sina Weibo, have allowed communities to come together for discussion and emotional support, while playing an important role for individuals, governments and organizations in publishing and exchanging information and expressing opinions. |
| T7 |
646-759 |
Sentence |
denotes |
However, limited research exists which studies the main concerns of citizens on social media during the pandemic. |
| T8 |
760-770 |
Sentence |
denotes |
OBJECTIVE: |
| T9 |
771-921 |
Sentence |
denotes |
To examine the main concerns raised and discussed by citizens on Sina Weibo, the largest social media platform in China, during the COVID-19 pandemic. |
| T10 |
922-930 |
Sentence |
denotes |
METHODS: |
| T11 |
931-1128 |
Sentence |
denotes |
This study uses a web crawler tool and a set of predefined search terms ("New Crown Pneumonia", "New Crown Virus" and "COVID-19") to investigate concerns raised by users of the Sina Weibo platform. |
| T12 |
1129-1332 |
Sentence |
denotes |
Textual information and the metadata (number of likes, comments, retweets, publishing time, and publishing location) of microblog posts, published between 1 December 2019 to 31 July 2020, were collected. |
| T13 |
1333-1505 |
Sentence |
denotes |
After segmenting the words of the text collected, we used a topic modeling technique, Latent Dirichlet Allocation (LDA), to identify the most common topics posted by users. |
| T14 |
1506-1858 |
Sentence |
denotes |
We analyzed the emotional tendency of topics, calculated the proportional distribution of topics, performed user' behavior analysis on the topics using data collected from the number of likes, comments and retweets, and studied the change in user concerns and differences in participation between citizens living in different regions of Mainland China. |
| T15 |
1859-1867 |
Sentence |
denotes |
RESULTS: |
| T16 |
1868-1982 |
Sentence |
denotes |
Based on the 203,191 eligible microblog posts collected, we identified 17 topics which were grouped into 8 themes. |
| T17 |
1983-2048 |
Sentence |
denotes |
Ranked by the level of attention paid to each, these topics were: |
| T18 |
2049-2631 |
Sentence |
denotes |
Pandemic statistics (26.8%); Domestic epidemic (18.1%); Epidemics in other countries around the world (13.9%); New Crown treatments (11.1%); Medical resources (10.9%); Economic shock (10.1%); Quarantine and investigation (9.12%); Patients' cry for help (8.61%); Work and production resumption (7.83%); Psychological influence (7.12%); Joint Prevention and Control (6.13%); Material donation (6.11%); Epidemics in neighboring countries (5.90%); Vaccine development (4.64%); Refueling and saluting towards anti-epidemic action (4.63%); Detection (4.39%); and Study resumption (3.39%). |
| T19 |
2632-2704 |
Sentence |
denotes |
The mean sentiment was positive for 11 topics and negative for 6 topics. |
| T20 |
2705-2856 |
Sentence |
denotes |
The topic with the highest mean of retweets was 'Domestic epidemic', while the topic with the highest mean of likes was 'Quarantine and investigation'. |
| T21 |
2857-2869 |
Sentence |
denotes |
CONCLUSIONS: |
| T22 |
2870-2969 |
Sentence |
denotes |
Citizens' concerns on social media are highly correlated with the evolution of the global pandemic. |
| T23 |
2970-3139 |
Sentence |
denotes |
During the COVID-19 pandemic, social media has provided a platform for Chinese government departments and organizations to better understand public concerns and demands. |
| T24 |
3140-3290 |
Sentence |
denotes |
Similarly, social media has provided a channel to disseminate information about epidemic prevention and has influenced public attitudes and behaviors. |
| T25 |
3291-3514 |
Sentence |
denotes |
Government departments, especially those which are health related, can create appropriate policies in a timely manner through the monitoring of social media platforms to guide public opinions and behaviors during epidemics. |
| T26 |
3515-3529 |
Sentence |
denotes |
CLINICALTRIAL: |
