THESIS DEFENSE: Jennifer Marlow
When
-
Where
NSH 3305
Description
Impression formation in online peer production
Jennifer Marlow
COMMITTEE
Laura Dabbish, CMU (Chair)
Jodi Forlizzi, CMU
Jim Herbsleb, CMU
Sara Kiesler, CMU
Scott Counts, Microsoft Research
DOCUMENT
https://www.dropbox.com/s/flqc3nzsse4m5pt/Marlow-DissertationDraft.pdf
ABSTRACT
Technology increasingly enables new forms of distributed and ad-hoc online collaboration known as peer production, where people contribute to projects from anywhere in the world. Some peer production environments now connect social media functionality directly to collaborative work artifacts, which provides participants with detailed information about unknown contributors’ work history, interests and interactions.
This visibility of activity provides informational signals from which individuals can make inferences about important characteristics of the people they interact with. However, the impact of the increased variety of information about collaborators and potential colleagues in a peer production setting is not well known.
Understanding how people form impressions of unknown others, including what information they utilize to reduce uncertainty about their targets, gives insight into why certain signals are used to infer qualities such as competence and interpersonal interaction style. At the same time, aspects of the presentation of visible information such as level of detail, ease of processing, and quality of information may also influence the cues that are used and the accuracy of inferences drawn.
My thesis investigates the process and outcomes of using activity traces for interpersonal impression formation in online peer production. I first conducted two interview studies with users of a social media enabled site supporting open source software development to understand what signals people use to form impressions about others’ expertise and attitudes, and how they used this information to make decisions about work contribution acceptance.
To understand how visual presentation of activity history influenced impressions of contributors and evaluation of work, I also conducted an experiment testing the effects of the amount of detail and quality of information presented on both the valence and persistence of initial impressions and bias towards an unknown worker as well as effort expended to correct the worker’s output on the task.
This work advances our understanding of when and how social networking information and activity traces influence the process of making sense of unknown contributors’ inherent qualities, and how this relates to work-related decision-making in peer production. The thesis also informs design principles for showcasing individuals’ activity history in collaborative production sites.