报告题目：Finding Useful Solutions in Online Knowledge Communities: A Theory-Driven Design and Multi-level Analysis
报告人：樊卫国 教授
邀请人：吴江宁 教授
时间及地点：2019年6月17日 上午10：00-11:30；大连理工大学经管学院B309
报告摘要：Online communities and social collaborative platforms have become an increasingly popular avenue for knowledge sharing and exchange. In these communities, users often engage in informal conversations responding to questions and answers, and over time produce a huge amount of highly unstructured and implicit knowledge. How to effectively manage the knowledge repository and identify useful solutions thus becomes a major challenge. In this study, we propose a novel text analytic framework to extract important features from online forums, and apply them to classify the usefulness of a solution. Guided by the design science research paradigm, we utilize a kernel theory of knowledge adoption model, which captures a rich set of argument quality and source credibility features as the predictors of information usefulness. We test our framework on two large scale knowledge communities: Apple Support Community and Oracle Community. Our extensive analysis and performance evaluation illustrate that the proposed framework is both effective and efficient in predicting the usefulness of solutions embedded in the knowledge repository. We highlight the theoretical implications of the study as well as the practical applications of the framework to other domains。
人物介绍：樊卫国主要从事社会计算、大数据及文本挖掘在商业领域的应用，商务智能与大数据的研究与开发, 社交媒体数据分析及用户行为，智慧健康等问题的研究； Management Science，MIS Quarterly，IEEE Transactions on Evolutionary Computation，IEEE Transactions on Knowledge and Data Engineering，ACM Transactions on Information Systems等期刊审稿人。任MIS Quarterly，Information & Management， Journal of AIS, Information Systems Journal 编委会成员。发表论文200余篇，其中有国际影响力的期刊论文80 余篇。谷歌学者引用次数超过7500次（H-index = 45）。全球谷歌学者引用排名，商务智能排名第8，商务数据分析第14，文本挖掘排名第44，社会计算第50。
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