Q&A forums are self-governing, prosocial platforms that rely on the quality of members’ contributions, which is decided by the person who poses the question. Drawing on the theories of relational bonds and social presence, we propose a research model that links people’s social presence and interpersonal relationships to their ability to provide quality contributions in Q&A forums. We test the impact of the two social bonds—internal and external—as well as the structural bonds in a Q&A forum. There are significant theoretical and practical ramifications to this study. For theory, the study explores the various potentials of social relationships in Q&A forums and extends the relational bonds theory. Additionally, social presence is included in the suggested paradigm, emphasizing both its enhancing and restricting aspects. For practice, managers should promote external bonding by offering more features that facilitate connectivity to other platforms, but they should dissuade excessive external bonding.

In this study, we investigate the role of medical lexicon of disclosed information and social capital on user-supportive behaviours in online health communities (OHC). We leverage text analytics to extract features to measure variables from patient.info to theorize a social capital-moderated model of user-supportive behaviours. Our results reveal that while cognitive capital (CC) has a negative relationship, structural capital (SC) has a positive relationship with user interaction (UI) and support helpfulness (SH). While the positive relationship between relational capital (RC) and UI is supported, that of RC and SH is not supported. Medical lexical density (MLD) is positively related to UI but the negative relationship with SH is not supported. Additionally, the negative moderation of MLD on relationships between SC and both UI and SH were supported. Furthermore, the positive moderation of MLD on the relationships between RC and both UI and SH are supported. However, while the negative moderation of MLD on the relationship between CC and SH is supported, that between CC and UI is not supported. The findings have implications for user health education and public health intervention aimed at promoting social support for medical information seeking.

IS researchers’ interest in interdisciplinary research is strong, given the widespread use of IT across disciplines. IS researchers have challenges identifying topics in the IS literature that offer interdisciplinary collaboration opportunities. While team collaboration research suggests that knowledge of shared concepts helps ensure team success, scant guidelines for achieving this goal exist. To address this gap, we demonstrate a text analytics tool focusing on “software piracy” as a case study. The tool analyzes abstracts, employing term-term co-occurrence to identify commonalities and exclusivity for a topic across disciplines. By assessing term prominence, intersection degrees, and shared clusters, the tool helps pinpoint potential interdisciplinary research foci. This approach identifies intersecting terminologies in software piracy and can be applied to other interdisciplinary phenomena in IS or other disciplines. Finally, the approach can be deployed to build multiple sets of relevant topic terms for a domain in different clusters for various collaborative communities.

Phishing attacks continue to be a concern for academia and practice. Practitioners ranked phishing attacks second to data breaches in a recent industry survey. For scholars, interest in understanding the factors that influence phishing susceptibility, defined as user vulnerability to phishing attacks, continues to grow. While prior research has identified either state (situational cues) or trait (technology use) factors that influence users’ response to phishing attacks, little previous research has investigated simultaneously user control of both state and trait factors on susceptibility to phishing. Additionally, the influence of users’ automatic or routine technology use, user traits, on phishing susceptibility has not been examined. We investigate the effects of users’ control of both state and trait factors on phishing susceptibility. Our results offer several interesting insights. Specifically, while routine technology use trait decreases phishing susceptibility, automatic technology use trait increases phishing susceptibility. Furthermore, while situational cues are related to phishing susceptibility, only users’ automatic technology use is related to susceptibility to phishing under message sender situational cues. Our findings provide practical insights for developing countermeasures that incorporate the level of control into training programs that target trainees with customised training aimed at preventing successful phishing attacks.