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A Machine Learning Approach to Cluster the users of Stack Overflow Forum

Publication Type : Conference Paper

Publisher : Springer, New Delhi

Source : Artificial intelligence and evolutionary algorithms in engineering systems

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Keywords : Clustering Naive users Surpassing users Bayesian information criterion

Campus : Coimbatore

School : School of Business

Department : Computer Science

Year : 2015

Abstract : Online question and answer (QA) forums are emerging as excellent learning platforms for learners with varied interests. In this paper, we present our results on the clustering of Stack Overflow users into four clusters, namely naive users, surpassing users, experts, and outshiners. This clustering is based on various metrics available on the forum. We use the X-means and expectation maximization clustering algorithms and compare the results. The results have been validated using internal, external, and relative validation techniques. The objective of this clustering is to be able to trace and predict the activity of a user on this forum. According to our results, majority of users (71 % of 40,000 users under consideration) fall in the ‘experts’ category. This indicates that the users in Stack Overflow are of high quality thereby making the forum an excellent platform for users to learn about computer programming.

Cite this Research Publication : Anusha J., Rekha V.S., Sivakumar P.B. (2015) A Machine Learning Approach to Cluster the Users of Stack Overflow Forum. In: Suresh L., Dash S., Panigrahi B. (eds) Artificial Intelligence and Evolutionary Algorithms in Engineering Systems. Advances in Intelligent Systems and Computing, vol 325. Springer, New Delhi

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