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arXiv · 1711.10768

Leveraging Conversation Structure on Social Media to Identify Potentially Influential Users

Dario De Nart·Dante Degl'Innocenti·Marco Pavan
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Abstract

Social networks have a community providing feedback on comments that allows to identify opinion leaders and users whose positions are unwelcome. Other platforms are not backed by such tools. Having a picture of the community's reactions to a published content is a non trivial problem. In this work we propose a novel approach using Abstract Argumentation Frameworks and machine learning to describe interactions between users. Our experiments provide evidence that modelling the flow of a conversation with the primitives of AAF can support the identification of users who produce consistently appreciated content without modelling such content.

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Dario De Nart, Dante Degl'Innocenti, Marco Pavan. 2017-11-29. Leveraging Conversation Structure on Social Media to Identify Potentially Influential Users. https://arxiv.org/abs/1711.10768

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