Online communities play a significant role in the digital era, spanning business organizations, various industries, and societal domains. Understanding the social roles within these communities, from influencers to followers and content providers, is crucial. This paper presents a machine learning-based technique for automating the detection and extraction of social roles from online communities. Using a deep recurrent neural network and word embedding model, the approach analyzes a dataset of over 1.2 million textual posts from an online higher education community in Australia, showcasing its applicability across different online communities to identify social roles, influence, and interactions.
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Wijenayake, Piyumini, et al. "Automated detection of social roles in online communities using deep learning." Proceedings of the 3rd International Conference on Software Engineering and Information Management. 2020.
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