Softening Online Extremes Using Network Engineering

The prevalence of dangerous misinformation and extreme views online has intensified since the onset of Israel-Hamas war on 7 October 2023. Social media platforms have long grappled with the challenge of providing effective mitigation schemes that can scale to the 5 billion-strong online population....

Full description

Bibliographic Details
Main Authors: Elvira M. Restrepo, Martin Moreno, Lucia Illari, Neil F. Johnson
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/10499247/
_version_ 1797193547783340032
author Elvira M. Restrepo
Martin Moreno
Lucia Illari
Neil F. Johnson
author_facet Elvira M. Restrepo
Martin Moreno
Lucia Illari
Neil F. Johnson
author_sort Elvira M. Restrepo
collection DOAJ
description The prevalence of dangerous misinformation and extreme views online has intensified since the onset of Israel-Hamas war on 7 October 2023. Social media platforms have long grappled with the challenge of providing effective mitigation schemes that can scale to the 5 billion-strong online population. Here, we introduce a novel solution grounded in online network engineering and demonstrate its potential through small pilot studies. We begin by outlining the characteristics of the online social network infrastructure that have rendered previous approaches to mitigating extremes ineffective. We then present our new online engineering scheme and explain how it circumvents these issues. The efficacy of this scheme is demonstrated through a pilot empirical study, which reveals that automatically assembling groups of users online with diverse opinions, guided by a map of the online social media infrastructure, and facilitating their anonymous interactions, can lead to a softening of extreme views. We then employ computer simulations to explore the potential for implementing this scheme online at scale and in an automated manner, without necessitating the contentious removal of specific communities, imposing censorship, relying on preventative messaging, or requiring consensus within the online groups. These pilot studies provide preliminary insights into the effectiveness and feasibility of this approach in online social media settings.
first_indexed 2024-04-24T05:42:08Z
format Article
id doaj.art-ec82f21eb59744b2be82fcacb72b7471
institution Directory Open Access Journal
issn 2169-3536
language English
last_indexed 2024-04-24T05:42:08Z
publishDate 2024-01-01
publisher IEEE
record_format Article
series IEEE Access
spelling doaj.art-ec82f21eb59744b2be82fcacb72b74712024-04-23T23:00:31ZengIEEEIEEE Access2169-35362024-01-0112557685578310.1109/ACCESS.2024.338885110499247Softening Online Extremes Using Network EngineeringElvira M. Restrepo0https://orcid.org/0000-0002-2172-6324Martin Moreno1Lucia Illari2https://orcid.org/0000-0001-7110-4040Neil F. Johnson3https://orcid.org/0000-0002-3224-3213Elliot School of International Affairs, George Washington University, Washington, DC, USAEngineering Department, Universidad de los Andes, Bogota, ColombiaPhysics Department, George Washington University, Washington, DC, USAPhysics Department, George Washington University, Washington, DC, USAThe prevalence of dangerous misinformation and extreme views online has intensified since the onset of Israel-Hamas war on 7 October 2023. Social media platforms have long grappled with the challenge of providing effective mitigation schemes that can scale to the 5 billion-strong online population. Here, we introduce a novel solution grounded in online network engineering and demonstrate its potential through small pilot studies. We begin by outlining the characteristics of the online social network infrastructure that have rendered previous approaches to mitigating extremes ineffective. We then present our new online engineering scheme and explain how it circumvents these issues. The efficacy of this scheme is demonstrated through a pilot empirical study, which reveals that automatically assembling groups of users online with diverse opinions, guided by a map of the online social media infrastructure, and facilitating their anonymous interactions, can lead to a softening of extreme views. We then employ computer simulations to explore the potential for implementing this scheme online at scale and in an automated manner, without necessitating the contentious removal of specific communities, imposing censorship, relying on preventative messaging, or requiring consensus within the online groups. These pilot studies provide preliminary insights into the effectiveness and feasibility of this approach in online social media settings.https://ieeexplore.ieee.org/document/10499247/Interventionsnetwork engineeringnetwork resilienceonline extremesscale
spellingShingle Elvira M. Restrepo
Martin Moreno
Lucia Illari
Neil F. Johnson
Softening Online Extremes Using Network Engineering
IEEE Access
Interventions
network engineering
network resilience
online extremes
scale
title Softening Online Extremes Using Network Engineering
title_full Softening Online Extremes Using Network Engineering
title_fullStr Softening Online Extremes Using Network Engineering
title_full_unstemmed Softening Online Extremes Using Network Engineering
title_short Softening Online Extremes Using Network Engineering
title_sort softening online extremes using network engineering
topic Interventions
network engineering
network resilience
online extremes
scale
url https://ieeexplore.ieee.org/document/10499247/
work_keys_str_mv AT elviramrestrepo softeningonlineextremesusingnetworkengineering
AT martinmoreno softeningonlineextremesusingnetworkengineering
AT luciaillari softeningonlineextremesusingnetworkengineering
AT neilfjohnson softeningonlineextremesusingnetworkengineering