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C ompared to traditional organizations, online community leadership processes and how leaders emerge are not well studied. Previous studies of online leadership have often identified leaders as those who administer forums or have high network centrality scores. Although communication in online communities occurs almost exclusively through written words, little research has addressed how the comparative use of language shapes community dynamics. Using participant surveys to identify leading online community members, this study analyzes a year of communication network history and message content to assess whether language use differentiates leaders from other core community participants. We contribute a novel use of textual analysis to develop a model of language use to evaluate the utterances of all participants in the community. We find that beyond communication network position-in terms of formal role, centrality, membership in the core, and boundary spanning-those viewed as leaders by other participants, post a large number of positive, concise posts with simple language familiar to other participants. This research provides a model to study online language use and points to the emergent and shared nature of online community leadership.

Increasingly abundant trace data provide an opportunity for information systems researchers to generate new theory. In this research commentary, we draw on the largely “manual” tradition of the grounded theory methodology and the highly “automated” process of computational theory discovery in the sciences to develop a general approach to computationally intensive theory development from trace data. This approach involves the iterative application of four general processes: sampling, synchronic analysis, lexical framing, and diachronic analysis. We provide examples from recent research in information systems.

Where do valuable contributions originate from in online innovation communities? Prior research provides conflicting answers. One view, consistent with a community of practice perspective, is that valued knowledge contributions are primarily provided by central participants at the core of a community. In contrast, other research—including work adopting an open innovation perspective—predicts that valuable ideas primarily emerge from peripheral participants, those at the margins of a field of knowledge who provide novel ideas and viewpoints. We integrate these contrasting perspectives by considering two distinct forms of position: social embeddedness (a core social position within the social network of participants interacting within a community) and epistemic marginality (a peripheral epistemic position based on the network of topics discussed by a community). Analyzing contributions by 697,412 participants of 52 Stack Exchange online innovation communities, we find that both participants who are socially embedded and participants who are epistemically marginal provide knowledge contributions that are highly valued by fellow community participants. Importantly, among epistemically marginal participants, those with high social embeddedness are more likely to provide contributions valued by the community; by virtue of their epistemic marginality, these participants may offer novel ideas while by virtue of their social embeddedness they may be able to more effectively communicate their ideas to the community. Thus, the production of knowledge in an online innovation community involves a complex interaction between the novelty emanating from the epistemic periphery and the social embeddedness required to make ideas congruent with existing social and epistemic norms.

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