A framework for quantifying controversy of social network debates using attributed networks: biased random walk (BRW)
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ORIGINAL ARTICLE
A framework for quantifying controversy of social network debates using attributed networks: biased random walk (BRW) Hanif Emamgholizadeh1 · Milad Nourizade1 · Mir Saman Tajbakhsh1 · Mahdieh Hashminezhad1 · Farzaneh Nasr Esfahani1 Received: 15 May 2020 / Revised: 26 August 2020 / Accepted: 19 October 2020 © Springer-Verlag GmbH Austria, part of Springer Nature 2020
Abstract All societies have been much more bipolar over the past few years, particularly after the emergence of online social networks and media. In fact, the gap between two ends of social spectrum is going to be even deeper after the spread of new media. In this circumstance, social polarization has been a growing concern among socialists and computer science experts because of the detrimental impact which online social networks can have on societies by adding fuel to the fire of extremism. Several researches were conducted for proposing measures to calculate controversy level in social networks, afterward, to reduce controversy among contradicting viewpoints, for example, by exposing opinions of one side to other side’s members. Most of the attempts for quantifying social networks’ controversy have considered the networks in their most primary forms, without any attributes. Although these kinds of researches provide platform-free algorithms to be used in different social networks, they are not able to take into account a great deal of useful information provided by users (node attributes). To surmount this shortcoming, we propose a framework to be utilized in different networks with different attributes. We propelled some Biased Random Walks (BRW) to find their path from start point to an initially unknown end point with respect to initial energy of start node and energy loss of nodes on the path. We extracted structural attribute of networks, using node2vec, and compared it with state-of-the-art algorithms, and showed its accuracy. Then, we extracted some content attributes of user and analyze their effects on the results of our algorithm. BRW is compared with another state-of-the-art controversy measuring algorithm. Then, its changes in different level of controversy in Persian Twitter are considered to show how it works in different circumstance. Keywords Social media · Polarization · Controversy · Social networks · Random walk
1 Introduction
* Hanif Emamgholizadeh [email protected] Milad Nourizade [email protected] Mir Saman Tajbakhsh [email protected] Mahdieh Hashminezhad [email protected] Farzaneh Nasr Esfahani [email protected] 1
Naqadeh, Islamic Republic of Iran
The surge of online social network and media in the first years of new century seemed to be so promising not only for personal relations but also for social and political freedom. Then, gradually the darker side emerged. Although in an individual level social network provides wider communication, users try to make relations with like-minded people (Barberá et al. 2015; Quattrociocchi et al. 2016). In social leve
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