Abstract
Through Online Social Networks, like Research Gate, Stack Exchange or Facebook, it’s easy to find a partner for cooperation, because Social Networks have the potential to connect thousands of people. To assist finding the right person for cooperation many of these networks have Recommender-Systems, but these systems mostly rely on the matching of keywords for each individual. This article shows on a conceptual level, that current Recommender-Systems for cooperation on Online Social Networks can be improved by additionally using personality for recommendations. Methods like Language Inquiry and Word Count (LIWC) can help to achieve this goal by presenting methods for an automated calculation of personality from user-generated content in these networks, without the need of questionnaires. Based on personality different cooperation types can be derived to improve recommendations for cooperation partners, leading to a better cooperation and therefore help to increase cooperation in Online Social Networks.
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Lamprecht, J., Siemon, D., Robra-Bissantz, S. (2016). Cooperation Isn’t Just About Doing the Same Thing – Using Personality for a Cooperation-Recommender-System in Online Social Networks. In: Yuizono, T., Ogata, H., Hoppe, U., Vassileva, J. (eds) Collaboration and Technology. CRIWG 2016. Lecture Notes in Computer Science(), vol 9848. Springer, Cham. https://doi.org/10.1007/978-3-319-44799-5_10
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