Rethinking lurking: invisible leading and following in a knowledge transfer ecosystem

Abstract

© 2015, Association for Information Systems. All rights reserved. The term lurker connotes a low-value role in online communities. Despite making up the majority of members, these invisible individuals are often cast as peripheral players who should be encouraged to participate more fully. We argue that the lurker concept is problematic and that online communities, and the roles associated with them, need to be reconceptualized. We report on a study of online communities in a New Zealand professional development program. We found that two knowledge broker types played key roles in transferring knowledge: connector-leaders, who had a strong online presence, and follower-feeders, who communicated largely invisibly, via side-channels. Despite their different online profiles, both brokers used “lurking” purposively to perform two sets of invisible online activities: managing the knowledge agenda, and mentoring/being mentored. These activities supported their roles as leaders and followers, and sustained a symbiotic relationship. Decisions to “lurk” arose from the need for these brokers to negotiate diverse boundaries: the boundaries of micro-culture associated with communication contexts, the theory-practice boundary, role boundaries, and the online-offline boundary. Combining the concept of polycontextuality with boundary spanning theory, we propose an alternative way of understanding both lurking and online communities: the three-tier knowledge transfer ecosystem (KTE), a system of engagement spaces comprising diverse online and offline contexts in which individuals make continual decisions to cross between less- or more-visible settings. The study illustrates how key phenomena may remain invisible without a shift in level of analysis, and how using an anachronistic concept to frame a study can unintentionally constrain its value.

Cite this work

No public copy is stored for this record, so only the metadata is cited.

Stored only when both papers are in the corpus — 11 citations exist upstream.

Papers that cite the same references — the relational fallback while embeddings are still backfilling.