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Abstract

The spread of misinformation on social media has become a major societal issue during recent years. In this work, we used the ongoing COVID-19 pandemic as a case study to systematically investigate factors associated with the spread of multi-topic misinformation related to one event on social media based on the heuristic-systematic model. Among factors related to systematic processing of information, we discovered that the topics of a misinformation story matter, with conspiracy theories being the most likely to be retweeted. As for factors related to heuristic processing of information, such as when citizens look up to their leaders during such a crisis, our results demonstrated that behaviors of a political leader, former US President Donald J. Trump, may have nudged people's sharing of COVID-19 misinformation. Outcomes of this study help social media platform and users better understand and prevent the spread of misinformation on social media.

Source

Journal of the Association for Information Science and Technology. 73(2022) no.5, S.726-737

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Abstract

The past 2 decades have witnessed the emergence of information as a scientific discipline and the growth of information schools around the world. We analyzed the current state of the iSchool community in the U.S. with a special focus on the evolution of the community. We conducted our study from the perspectives of acquiring talents and producing research, including the analysis on iSchool faculty members' educational backgrounds, research topics, and the hiring network among iSchools. Applying text mining techniques and social network analysis to data from various sources, our research revealed how the iSchool community gradually built its own identity over time, including the growing number of faculty members who received their doctorates from the field that studies information, the deviation from computer science and library science, the rising emphasis on the intersection of information, technology, and people, and the increasing educational and research homogeneity as a community. These findings suggest that iSchools in the U.S. are evolving into a mature and independent discipline with a more established identity.

Source

Journal of the Association for Information Science and Technology. 68(2017) no.5, S.1266-1277

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Abstract

This article presents a rare insight into the migration of municipality record-keeping databases. The migration of a database for preservation purposes poses Online health communities (OHCs) have been major resources for people with similar health concerns to interact with each other. They offer easily accessible platforms for users to seek, receive, and provide supports by posting. Taking the advantage of text mining and machine learning techniques, we identified social support type(s) in each post and a new user's support needs in an OHC. We examined a user's first-time support-seeking experience by measuring both quantity and quality of received support. Our results revealed that the amount and match of received support are positive and significant predictors of new users' continued engagement. Our outcomes can provide insight for designing and managing a sustainable OHC by retaining users.

Source

Journal of the Association for Information Science and Technology. 72(2021) no.6, S.710-722

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Abstract

Performance assessment is ubiquitous and crucial in people analytics. Scientific impact, particularly, plays a significant role in the academia. This paper attempts to understand researchers' career trajectories by considering the research community as a social network, where individuals build ties with each other via coauthorship. The resulting linkage facilitates information flow and affects researchers' future impact. Consequently, we systematically investigate the career trajectories of researchers with respect to research impact using the social capital theory as our theoretical foundation. Specifically, for early-stage and mid-career academics, we find that connections with prominent researchers associate with greater impact. Brokerage positions, in addition, are beneficial to a researcher's research impact in the long run. For senior researchers, however, the only social network feature that significantly affects their future impact is the reputation of their recently built ties. Finally, we build predictive models on future research impact which can be leveraged by both organizations and individuals. This paper provides empirical evidence for how social networks provide signals on researchers' career dynamics guided by social capital theory. Our findings have implications for individual researchers to strategically plan and promote their careers and for research institutions to better evaluate current as well as prospective employees.

Source

Journal of the Association for Information Science and Technology. 72(2021) no.4, S.454-472