Multi-label classification of member participation in online innovation communities

Steven Debaere, Kristof Coussement () and Tom de Ruyck
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Kristof Coussement: LEM - Lille économie management - UMR 9221 - UA - Université d'Artois - UCL - Université catholique de Lille - Université de Lille - CNRS - Centre National de la Recherche Scientifique

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Abstract: Online innovation communities are defined as internet-based platforms for communication and exchange among customers interested in building innovations for a given product or technology. As firms recognize an online innovation community as a valuable resource for integrating external consumer knowledge into innovation processes, they increasingly ignore to build long-term interactions and collaborations. However, in the pursuit of a long-term community, moderators face enormous challenges, especially due to inferior member participation. Inferior member participation, whether in the form of inferior participation quantity, quality and/or emotionality, produces a community with minimal activity, unhelpful content and a nonconstructive atmosphere, respectively. Because members can be associated with multiple labels of inferior participation behavior simultaneously, the paradigm of multi-label (ML) classification methodology naturally emerges, which associates each member of interest with a set of labels instead of a single label as known in traditional classification problems. Using 1407 members of 7 real-life innovation communities, this study explores 10 state-of-the-art ML algorithms in an extensive experimental comparison to explore the benefit of ML classification methodology. We advance literature by demonstrating a novel application for ML classification adoption in the domain of online innovation communities, while comparing ML classifiers in the smallest possible scenario of 3 labels. The results indicate the effectiveness of the ML classification methodology for inferior member participation prediction, gives insights into ML classifiers' performance and discusses paths for future research.

Keywords: Analytics; Multi-label classification; Innovation communities; Member participation (search for similar items in EconPapers)
Date: 2018-10-16
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Citations: View citations in EconPapers (6)

Published in European Journal of Operational Research, 2018, 270 (2), pp.761-774. ⟨10.1016/j.ejor.2018.03.039⟩

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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-02990807

DOI: 10.1016/j.ejor.2018.03.039

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