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....
Main Authors: | , , , |
---|---|
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 |