Abstract

Online discussion in form of written comments is a core component of many social media platforms. It has attracted increasing attention from academia, mainly because theories from social sciences can be explored at an unprecedented scale. This interest has led to the development of statistical models which are able to characterize the dynamics of threaded online conversations.In this paper, we review research on statistical modeling of online discussions, in particular, we describe current generative models of the structure and growth of discussion threads. These are parametrized network formation models that are able to generate synthetic discussion threads that reproduce certain features of the real discussions present in different online platforms. We aim to provide a clear overview of the state of the art and to motivate future work in this relevant research field.

Highlights

  • The success of the Internet has generated a wide variety of platforms for computer-mediated communication

  • We focus on models that incorporate a fundamental ingredient of online discussion threads: their reply structure

  • 7 Open research challenges We have presented several models that are able to reproduce many of the characteristics of online discussion threads in platforms of very different nature

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Summary

Introduction

The success of the Internet has generated a wide variety of platforms for computer-mediated communication. Discussions on the Internet commonly occur as a exchange of written messages among two or more participants. In this way, conversations are often represented as threads, which are initiated by a user posting a starting message (hereafter post) and users send replies to either the post or the existing replies. Conversations are often represented as threads, which are initiated by a user posting a starting message (hereafter post) and users send replies to either the post or the existing replies Given this sequential posting behavior, online discussion threads follow a tree network structure. Previous and recent research has analyzed this network structure of online discussions for different and relevant purposes, e.g. the resolution of problems in e-learning platforms [2], the response of

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