Title

Network Semantic Segmentation With Application To Github

Keywords

Community detection; Github social coding; Social networks

Abstract

In this paper we introduce the concept of network semantic segmentation for social network analysis. We consider the GitHub social coding network which has been a center of attention for both researchers and software developers. Network semantic segmentation describes the process of associating each user with a class label such as a topic of interest. We augment node attributes with network significant connections and then employ machine learning approaches to cluster the users. We compare the results with a network segmentation performed using community detection algorithms and one executed by clustering with node attributes. Results are compared in terms of community diversity within the semantic segments along with topic coverage.

Publication Date

12-1-2018

Publication Title

Proceedings - 2018 International Conference on Computational Science and Computational Intelligence, CSCI 2018

Number of Pages

1281-1284

Document Type

Article; Proceedings Paper

Personal Identifier

scopus

DOI Link

https://doi.org/10.1109/CSCI46756.2018.00247

Socpus ID

85078514278 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/85078514278

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