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Data Analysis and Knowledge Discovery  2018, Vol. 2 Issue (12): 12-22    DOI: 10.11925/infotech.2096-3467.2018.0393
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Identifying Useful Information from Open Innovation Community
He Li,Linlin Zhu(),Min Yan,Jincheng Liu,Chuang Hong
School of Management, Jilin University, Changchun 130022, China
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[Objective] The paper aims to identify useful message from open innovation community with numerous redundant and low quality information. [Methods] First, we retrieved 23,137 users’ comments on programming bugs from the official Xiaomi MIUI Forum based on the information adoption model. Then, we applied binary logistic regression method to explore factors affecting the usefulness of these comments. [Results] The timeliness of information had positive impact on their usefulness, the integrity of information also affected their usefulness, and the semantics of information had negative effects on their usefulness. The users’ previous experience did not influence the usefulness of information. However, users’ previous contribution had positive effects on the usefulness of information. [Limitations] The research data was collected from small portion of one community, which might yield biased results. [Conclusions] This paper could help us effectively identify usefulness information from open innovation communities.

Key wordsOpen Innovation Community      Information Adoption Model      LDA Topic Model     
Received: 08 April 2018      Published: 16 January 2019

Cite this article:

He Li,Linlin Zhu,Min Yan,Jincheng Liu,Chuang Hong. Identifying Useful Information from Open Innovation Community. Data Analysis and Knowledge Discovery, 2018, 2(12): 12-22.

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