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This study aimed to examine the impact of perceived risks of COVID-19 and users’ intention to continually use social media for COVID-19 information, thereby revealing social media users’ perceptions and behaviors regarding the pandemic.

The Health Belief Model was used to develop the research model. Data were collected from social media users in Korea using an online survey.

The findings showed that social media users’ intention to continually use social media for COVID-19 information explained 46.5% of the variance in their perceived severity, perceived susceptibility, perceived benefits, and perceived barriers. The degree of impact and relationships varied across the constructs. Two age groups were examined, and it transpired that perceived risks and perceived use were more highly recognized by young users than old users.

This study focused on Korean social media users, providing valuable insights but limiting its generalizability. The proposed research model and methodology can include participants from various countries or cultures to enhance global relevance and diversified perspectives on how perceived risks impact social media use for health information.

This study’s findings can be used to provide tailored health information services to those with different levels of perceived risks, social media use, and different age groups.

This study adopted the Health Belief Model to understand users’ perceptions of COVID-19 information on social media and examined users’ intentions to continue using social media as a channel for COVID-19 information.

This study investigated information needs on COVID-19 by identifying topics discussed on social questions and answers (Q&A) about daily routines, problems, and health issues for survival. A layered model of contexts for everyday life information seeking (ELIS) was adapted for interpreting topics to better understand the contexts in which users could relate information needs.

Questions and answers posted on Naver Knowledge-iN were collected and analyzed during the first nine months following the outbreak. Time distribution, topic modeling, and association rule mining were applied to examine the topics on COVID-19 and their temporal variation.

Numerous topics related to the cognitive context (symptoms and masks) and situational contexts (international affairs, financial support, study, and work) were discovered. Topics related to social context were discussed moderately, but the number of questions on this topic increased with time. Strong associations were observed between terms related to symptoms, indicating their importance as a COVID-19 topic in health.

This study investigated topics of information needs using social Q&A data in which not only information inquiry but also information sharing coexist. The findings can help bridge the theory of ELIS to topic modeling in practice. The insights gained from this study can be used by information service providers for developing guidance and programs about how to survive during a pandemic.

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-10-2021-0547.

This study aims to investigate the nature and evolution of online communities in the early stages of their life cycles. The authors analyze the topics of discussions in an online community to identify issues related to community development. The authors also compare the topics of exemplary questions that founding members believed to be asked with the real questions based on members' information needs.

The authors use Medical Sciences Stack Exchange, a health Q&A community of Stack Exchange, which requires four stages of development: definition, commitment, private beta and public beta. The authors collect postings of discussions and health questions in the first three stages, perform a content analysis of the postings and analyze the topics of discussions and health questions.

The authors find that the topics of discussions evolved dynamically with the issues of community governance, role as a medical/health community, members and roles, content management, quality control and community design. The authors also find that the real questions included more specific and diverse issues than the exemplary questions that founding members expected.

Theoretically, this study tests the community life cycle model in an online community that has explicit phase markers. The findings could shed light on community development and help prioritize issues to solve and decisions to make in its early stages. Additionally, this study focuses on the challenges and concerns in online health community building and solutions generated by collective efforts that could influence health communications in online communities.

The purpose of this paper is to determine employment satisfaction of middle-aged and older workers who obtain a job after their initial retirement, and describe factors affecting employment satisfaction among workers focusing on family and employment types, and their mediating effects.

This study performed a secondary data analysis on data from the Korean Longitudinal Study of Aging (fifth wave of KLoSA) of the Korea Employment Information Service. The author used data from 1,307 middle-aged and older workers who obtained a new job after leaving the previous workplace from the 2014 KLoSA, and determined their employment satisfaction, family type and employment type.

In this study, high scores were indicated in turnover intentions of the participants, and job stability presented was lowest in the subcategories of employment satisfaction. Employment type showed a significant mediation effect between dwelling type and re-employment satisfaction (p<0.05).

Middle-aged workers are a key human resource for economic growth in South Korea, which is faced with a “super aging” population. Recently, international society has encountered the same problems of low-birth rate and aging in their economically viable/or engaged. Our society and its members should realize the changes in population structure facing the world today and find effective strategies to stabilize employment among middle-aged workers. This study provides evidence for one of the differing perspectives on understanding employment turnover in middle-aged workers.

The South Korean Government could use this study’s findings in formulating a strategy concerning family types that improves re-employment satisfaction among middle-aged and older workers. Also, the path of mediation effects, such as choice of employment type, will need to apply to a strategy of work stability for middle-aged and older workers.

Through a two-stage survey, this paper examines how researchers judge the quality of answers on ResearchGate Q&A, an academic social networking site.

In the first-stage survey, 15 researchers from Library and Information Science (LIS) judged the quality of 157 answers to 15 questions and reported the criteria that they had used. The content of their reports was analyzed, and the results were merged with relevant criteria from the literature to form the second-stage survey questionnaire. This questionnaire was then completed by researchers recognized as accomplished at identifying high-quality LIS answers on ResearchGate Q&A.

Most of the identified quality criteria for academic answers—such as relevance, completeness, and verifiability—have previously been found applicable to generic answers. The authors also found other criteria, such as comprehensiveness, the answerer's scholarship, and value-added. Providing opinions was found to be the most important criterion, followed by completeness and value-added.

The findings here show the importance of studying the quality of answers on academic social Q&A platforms and reveal unique considerations for the design of such systems.

With the growth in popularity of academic social networking sites, evaluating the quality of the academic information they contain has become increasingly important. Users' evaluations of this are based on predefined criteria, with external factors affecting how important these are seen to be. As few studies on these influences exist, this research explores the factors affecting the importance of criteria used for judging high-quality answers on academic social Q&A sites.

Scholars who had recommended answers on ResearchGate Q&A were asked to complete a questionnaire survey to rate the importance of various criteria for evaluating the quality of these answers. Statistical analysis methods were used to analyze the data from 215 questionnaires to establish the influence of scholars' demographic characteristics, the question types, the discipline and the combination of these factors on the importance of each evaluation criterion.

Particular disciplines and academic positions had a significant impact on the importance ratings of the criteria of relevance, completeness and credibility. Also, some combinations of factors had a significant impact: for example, older scholars tended to view verifiability as more important to the quality of answers to information-seeking questions than to discussion-seeking questions within the LIS and Art disciplines.

This research can help academic social Q&A platforms recommend high-quality answers based on different influencing factors, in order to meet the needs of scholars more effectively.

The current study aims to investigate the factors that impact the feedback received on answers to questions in social Q&A communities and whether the expertise-required question influences the role of these factors on the feedback.

To understand the antecedents and consequences that influence the feedback received on answers to online community questions, the elaboration likelihood model (ELM) is applied in this study. The authors use web data crawling methods and a combination of quantitative analyses. The data for this study came from Zhihu; in total, 353,775 responses were obtained to 1,531 questions, ranging from 49 to 23,681 responses per question. Each answer received 0 to 113,892 likes and 0 to 6,250 comments.

The answers' cognitive and emotional components and the answerer's influence positively affect user feedback behavior. In addition, the expertise-required question moderates the effects of the answer's cognitive component and emotional component on the user feedback, moderating the effects of the answerer's influence on the user approval feedback.

This study builds upon a limited yet growing body of literature on a theme of great relevance to scholars, practitioners and social media users concerning the effects of the connotation of answers (i.e. their cognitive and emotional components) and the answerer's influence on user feedback (i.e. approval and collaborative feedback) in social Q&A communities. The authors further consider the moderating role of the domain expertise required by the question (expertise-required question). The ELM model is applied to explore the relationships between questions, answers and feedback. The findings of this study add a new perspective to the research on user feedback and have implications for the management of social Q&A communities.