Informal learning in online knowledge communities: Predicting community response to visitor inquiries

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Abstract

Informal learning in online knowledge communities (OKCs) comprises visitor inquiries on specific topics. Learning can occur only if the OKC adequately respond. This study aims to predict OKC response, using a social learning analytics approach based on computational linguistics and Bakhtin’s theory of dialogism. Observing the blog topic (cooking vs. politics & economics) and the visitor inquiry format (off-topic vs. on-topic), a field experiment with a 2 × 2 factorial design was conducted on a sample of N = 68 blogger communities with a total of 25,303 members. For the entire sample, the community response was influenced only by the inquiry format. In a separate examination of experimental groups, only for one examined topic (cooking) this remained true, while for the other (politics & economics) the community response only depended on the previously established dialog quality. The findings suggest identification criteria for responsive communities, which can support OKC integration in learning environments.

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Nistor, N., Dascălu, M., Stavarache, L. L., Serafin, Y., & Trăușan-Matu, Ștefan. (2015). Informal learning in online knowledge communities: Predicting community response to visitor inquiries. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9307, pp. 447–452). Springer Verlag. https://doi.org/10.1007/978-3-319-24258-3_38

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