Abstract
This work explores simulations of polarized discussions from a general and theoretical premise. Specifically the question of whether a plausible avenue exists for a subgroup in an online social network to find a disagreement beneficial and what that benefit could be. A methodological framework is proposed which represents key factors that drives social media engagement including the iterative accumulation of influence and the dynamics for the asymmetric treatment of messages during a disagreement. It is shown that prior to a polarization event a trend towards a more uniform distribution of relative influence is achieved which is then reversed by the polarization event. The reasons for this reversal are discussed and how it has a plausible analogue in real world systems. A pair of inoculation strategies are proposed which aim at returning the trend towards uniform influence across users while refraining from violating user privacy (by remaining topic agnostic) and from user removal operations.
Highlights
This work explores simulations of polarized discussions from a general and theoretical premise
The topic of polarization in societies is a problem of major concern and this problem has a different platform upon which it can develop with the availability of online social networks
The topics for polarization can come from a wide array of different areas of society such as political discourse[5,6], where increases are recently being observed in the US7–9
Summary
This work explores simulations of polarized discussions from a general and theoretical premise. Key differentiators are the low cost of communication with large groups of people over long distances and another often overlooked feature is the historical track record of popular content which can be on public display[1,2] This last point is very important for the users who dedicate a substantial amount of their time as they are indicators for the rank of influence (‘views’, ‘re-tweets’, ‘likes’, etc). Our approach to addressing incentives does not assume that the contents of a message can be examined in order to adhere to privacy advocacy[24] or depend upon a label on its state It explores methods in which polarization can be reduced, and reversed without the need to remove nodes. Message exchanges in online social networking platforms where users are exposed to a pool of content and their sharing of content and can be considered equivalent to the popular retweet mechanism, is in effect an amplification of content by the original author in which various authorship credit features exist[25]
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