TY - CHAP T1 - Levels of trace data for social and behavioural science research T2 - Big Data Factories: Collaborative Approaches Y1 - 2017 A1 - Kevin Crowston ED - Sorin Matei ED - Sean Goggins ED - Nicolas Jullien AB -

The explosion of data available from online systems such as social media is creating a wealth of trace data, that is, data that record evidence of human activity. The volume of data available offers great potential to advance social and behavioural science research. However, the data are of a very different kind than more conventional social and behavioural science data, posing challenges to use. This paper adopts a data framework from Earth Observation science and applies it to trace data to identify possible issues in analyzing trace data. Application of the framework also reveals issues for sharing and reusing data.

JF - Big Data Factories: Collaborative Approaches PB - Springer Nature SN - 978-3-319-59186-5 ER - TY - Generic T1 - Lessons from volunteering and free/libre open source software development for the future of work T2 - IFIP Working Group 8.2 Working Conference: Researching The Future Y1 - 2011 A1 - Kevin Crowston JF - IFIP Working Group 8.2 Working Conference: Researching The Future PB - Springer CY - Turku, Finland ER - TY - Generic T1 - Leadership in self-managing virtual teams Y1 - 2010 A1 - Kevin Crowston A1 - Heckman, Robert A1 - Misiolek, Nora AB - In this paper, we present a theory of leadership in self-managing virtual teams. We are particularly interested in self-managing virtual teams because self-management seems to be a common phenomenon in teams that interact primarily through information technology (so-called virtual teams). Building on leadership theory and structuration theory, the theory describes leadership as a process that results in the reinforcement, creation and evolution of ongoing structures and distinguishes between two types of leadership. We identify first-order leadership as leadership that works within and reinforces existing structures to elicit and guide group contributions. We define second-order leadership as behavior that effects changes in the structure that guides group action. We argue that second-order leadership is enabled by first-order leadership, is therefore action embedded, and is grounded in processes that define the social identity of the team. We propose that effective self-managing virtual teams will exhibit a paradoxical combination of shared, distributed first-order leadership complemented by strong, concentrated, and centralized second-order leadership. We conclude by presenting a set of research questions and suggestions for future research. PB - Syracuse University School of Information Studies ER - TY - CONF T1 - Language and power in self-organizing distributed teams T2 - OCIS Division, Academy of Management Conference Y1 - 2006 A1 - Li, Qing A1 - Kevin Crowston A1 - Heckman, Robert A1 - James Howison KW - FLOSS AB - In this paper, a comparative case study is conducted to explore the way power is expressed and exercised through language use in distributed or virtual teams. Our research questions are “how is power expressed in online interactions in self-organizing distributed teams, in a context without formal authority or hierarchy?” and “What effects do expressions of power have on team outcomes?” To fully understand the role of power in self-organizing teams, we apply an input-process-output model on two open source projects-one successful and the other less successful. Two set of codes (source of power and power mechanism) are drawn from the data, and different power patterns interestingly show up between them. The findings lead us to speculate that strong, centralized leadership, the assertive exercise of power, and direct language may contribute to effectiveness in FLOSS teams. And the relevant conclusions and suggestions are provided for further research. JF - OCIS Division, Academy of Management Conference CY - Atlanta, GA ER -