LitCovid-sentences  

PubMed:33151894 JSONTXT 14 Projects

Annnotations TAB TSV DIC JSON TextAE

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: