The state of social science research on COVID-19

The impact and management of internet-based public opinion dissemination during emergencies: A case study of Baidu News during the first wave of coronavirus disease 2019 (COVID-19)

BACKGROUND AND AIMS

The coronavirus disease 2019 (COVID-19) public health emergency has had a huge impact worldwide. We analyzed news headlines and keywords from the initial period of COVID-19, and explored the dissemination timeline of news related to the epidemic, and the impact of Internet-based media on the public using lifecycle theory and agenda-setting theory. We aimed to explore the impact of Baidu news headlines on public attention during the first wave of COVID-19, as well as the management mechanism of regulatory departments for social public opinion.

METHODS

We searched Baidu News using the keywords "Novel Coronavirus" and "COVID-19" from 8 January to 21 February 2020, a total of 45 days, and used Python V3.6 to extract news samples during the first wave of the epidemic. We used text analysis software to structurally process captured news topics and content summaries, applied VOSviewer V6.19 and Ucinet V6.0 to examine key aspects of the data.

RESULTS

We analyzed the impact of Baidu News headlines on social opinion during the first wave of COVID-19 in the budding, spread, and outbreak stage of the information lifecycle. From clustering visualization and social network analysis perspectives, we explored the characteristics of Baidu News during the initial stage of the COVID-19. The results indicated that agenda-setting coverage through online media helped to mitigate the negative impact of COVID-19. The findings revealed that news reporting generated a high level of public attention toward a specific emergency event.

CONCLUSIONS

The public requires accurate and objective information on the progress of COVID-19 through Baidu News headlines to inform their planning for the epidemic. Meanwhile, government can enhance the management mechanism of news dissemination, correct false and inaccurate news, and guide public opinion in a positive direction. In addition, timely official announcements on the progress of the COVID-19 outbreak and responses to matters of public concern can help calm tensions and maintain social stability.

Believing in science: Linking religious beliefs and identity with vaccination intentions and trust in science during the COVID-19 pandemic

Despite evidence supporting numerous scientific issues (e.g. climate change, vaccinations) many people still doubt the legitimacy of science. Moreover, individuals may be prone to scepticism about scientific findings that misalign with their ideological beliefs and identities. This research investigated whether trust in science (as well as government and media) and COVID-19 vaccination intentions varied as a function of (non)religious group identity, religiosity, religion-science compatibility beliefs, and/or political orientation in two online studies (N = 565) with university students and a Canadian community sample between January and June 2021. In both studies, vaccination intentions and trust in science varied as a function of (non)religious group identity and beliefs. Vaccine hesitancy was further linked to religiosity through a lack of trust in science. Given the ideological divides that the pandemic has exacerbated, this research has implications for informing public health strategies for relaying scientific findings to the public and encouraging vaccine uptake in culturally appropriate ways.

A scientometric approach to psychological research during the COVID-19 pandemic

During the COVID-19 pandemic, modern science demonstrated its ability to respond well to the health crisis by publishing useful and reliable information. This disease has also led to an increase in psychological publications in this field. However, most scientometric studies have focused on medical aspects, and social science research has been neglected. Therefore, to fill this research gap, we analyzed the research on COVID-19 in the field of psychology to provide an insight into the perspective, research fields, and international collaborations. Data were collected from the Web of Science database and analyzed using Citespace and Bibliometrix (Biblioshiny). The overall performance of the documents was described, and then keyword co-occurrence and co-authorship networks were visualized. Fifteen main clusters were formed by drawing document co-citation network. The result indicates that Anxiety, mental health, delirium, loneliness, and suicide were important topics for researchers. Considering the special conditions that COVID-19 created for human societies, perhaps one of the most important subjects in the field of health is psychological studies. Using the results of this study, psychology researchers can identify their potential colleagues and research gaps in the subject of Covid-19.

Comment on the article: The state of social science research on COVID‑19

A well-written and interesting article was published on November 21, 2021. Future relevant studies, however, may be improved by implementing (1) a framework that outlines the overall research; (2) an author-weighted scheme (AWS) that accurately quantifies the contributions of entities to articles; and (3) a more appropriate size for the nodes representing the proportional counts for each entity in social network analysis (SNA). VOSviewer was used to construct and visualize the scientometric networks and the relation-based analyses included three categories: (1) citation relations, (2) word cooccurrences, and (3) coauthorship relations. Nevertheless, the counts for each topical entity have not been consistently integrated. As a result, the nodes of the keyword co-occurrence network are large when compared to the number of connections between the entities or terms (i.e., the total number of relationships between co-occurring terms or entities). Additionally, all weighted counts in keywords (or the total link strength of a country/region) should equal the total number of documents (e.g., n = 9954 in that article). This would lead to biases in the calculation of publications (or citations) for entities, as is common in traditional SNA. This node illustrates a study framework and a couple of AWSs (i.e., equal and nonequal AWSs) to improve the article, and discusses the need to understand the requirement that the total centrality degree in SNA equals the total number of documents (or citations).

A bibliometric analysis of linguistic research on COVID-19

Research on COVID-19 has drawn the attention of scholars around the world since the outbreak of the pandemic. Several literature reviews of research topics and themes based on scientometric indicators or bibliometric analyses have already been conducted. However, topics and themes in linguistic-specific research on COVID-19 remain under-studied. With the help of the CiteSpace software, the present study reviewed linguistic research published in SSCI and A&HCI journals to address the identified gap in the literature. The overall performance of the documents was described and document co-citations, keyword co-occurrence, and keyword clusters were visualized via CiteSpace. The main topic areas identified in the reviewed studies ranged from the influences of COVID-19 on language education, and speech-language pathology to crisis communication. The results of the study indicate not only that COVID-19-related linguistic research is topically limited but also that insufficient attention has been accorded by linguistic researchers to Conceptual Metaphor Theory, Critical Discourse Analysis, Pragmatics, and Corpus-based discourse analysis in exploring pandemic discourses and texts.