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Abstract

Social media provides a fertile ground for expertise location. The public nature of the data supports expertise inference with little privacy infringement and, in addition, presentation of direct and detailed evidence for an expert’s skillfulness in the queried topic. In this work, we study the use of social media for expertise evidence. We conducted two user surveys of enterprise social media users within a large global organization, in which participants were asked to rate anonymous experts based on artificial and real evidence originating from different types of social media data. Our results indicate that the social media data types perceived most convincing as evidence are not necessarily the ones from which expertise can be inferred most precisely or effectively. We describe these results in detail and discuss implications for designers and architects of expertise location systems.

Part of the research was conducted while working at IBM Research.

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Notes

  1. 1.

    https://www.jivesoftware.com/.

  2. 2.

    https://www.yammer.com/.

  3. 3.

    http://www-03.ibm.com/software/products/en/conn.

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Correspondence to Arnon Yogev .

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Yogev, A., Guy, I., Ronen, I., Zwerdling, N., Barnea, M. (2015). Social Media-Based Expertise Evidence. In: Boulus-Rødje, N., Ellingsen, G., Bratteteig, T., Aanestad, M., Bjørn, P. (eds) ECSCW 2015: Proceedings of the 14th European Conference on Computer Supported Cooperative Work, 19-23 September 2015, Oslo, Norway. Springer, Cham. https://doi.org/10.1007/978-3-319-20499-4_4

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