Knowledge sharing on Q&A fora: challenges of automated interaction analysis

Master thesis (2020)

Authors

P.A. Ruben Applied Sciences

Contributors

E. Kalmar Science Education and Communication - AS (mentor)
A. Labetski Urban Data Science - Architecture and the Built Environment (mentor)
M.C.A. van der Sanden Science Education and Communication - AS (graduation committee member)
G.A.K. Arroyo Ohori Urban Data Science - Architecture and the Built Environment (graduation committee member)
C. Wehrmann Science Education and Communication - AS (graduation committee member)
Faculty
Applied Sciences, Applied Sciences
Copyright: © 2020 Pablo Ruben
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Published Date

07-09-2020

Language

English

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Faculty

Applied Sciences

Abstract

Q\&A fora have developed into a precious tool for online knowledge exchange. Being community-driven, openly accessible and free, getting an answer to a complicated question can nowadays be a matter of minutes. This research investigates the specific case of gis.stackexchange, a technical Q&A forum used by Geographic Information Systems professionals. A central topic is the interaction between users. Based on existing research, an automated approach is elaborated and a big data analysis is performed. Also, a link between the outcomes and self-reflective behaviour found on the community meta forum is established. Factors positively influencing interaction as defined by the approach are identified (implication of the author(s), presence of images and code snippets). Furthermore, weaknesses such as the low share of interactions associated to an alteration (of the original post) are also discussed. These outcomes eventually lead to a series of recommendations for the forum itself and related formats.