Monthly Magazine Logo

Table of Content

Algorithmic Amplification And Radicalisation

Posted 24 Mar 2025

Updated 27 Mar 2025

4 min read

Why in the news?

Recently, experts have raised concerns regarding social media algorithms having the potential to amplify and spread extremism.

Understanding Social Media Algorithmic Amplification

  • Social media algorithms: These are computerized rules that examine user behaviour and rank content based on interactive metrics such as likes, comments, shares, timelines etc. 
    • It uses machine learning models to make customized recommendations.
    • It works as amplifiers because posts with higher engagement, shares, likes etc., alongwith hashtags, quickly tend to gain popularity and emerge as viral trends.
  • Algorithmic Radicalisation: It is the idea that algorithms on social media platforms drive users towards progressively more extremist propaganda and polarizing narratives
    • It then influences their ideological stances, exacerbating societal divisions, promoting disinformation, bolstering influence of extremist groups etc. 
    • It reflects social media algorithms, which are intended to boost user interaction, inadvertently construct echo chambers and filter bubbles, confirming users' pre-existing beliefs, leading to confirmation bias, group polarization etc.
    • It shows how social media platforms coax users into ideological rabbit holes and form their opinions through a discriminating content curation model.
Description: A diagram of a diagram of a social media network

Description automatically generated with medium confidence

Challenges in curbing Algorithmic Radicalization

  • Complex mechanisms involved: The opacity of algorithms used in social media present challenges in addressing extremist contents.
    • Social media algorithms work as 'black boxes', in which even some developers fully don't understand the underlying processes for recommending certain content.
    • E.g., complexity of TikTok's "For You" page's operational mechanics, limits the mitigation of its algorithmic bias.
  • Modulated content: Extremist groups change their radical contents to euphemisms or symbols to evade detection systems.
    • E.g., IS and al-Qaeda uses coded language and satire to avoid detection.
  • Moderation vs. free speech: Maintaining the right balance between effective content moderation and free speech is a complex issue.
    • Extremist groups exploit this delicate balance by ensuring that their contents remain within the permissible limits of free speech, while still spreading divisive ideologies.
  • Failure in accounting local context: Extremist contents are generated from the socio-political undercurrents in a specific country, and algorithms deployed globally often fail to account for these local socio-cultural contexts, exacerbating the problem.
  • Lack of international regulation and cooperation: Countries primarily view radical activities from their national interest rather than from the perspective of global humanity.

Steps taken to curb Algorithmic Radicalisation 

Global steps 

  • European Union's (EU's) Digital Services Act 2023 requires social media apps to disclose how their algorithms work and allows independent researchers to assess their impact on users.
  • Artificial Intelligence (AI)-driven moderation: E.g., YouTube's machine-learning model, 2023, reduced flagged extremist videos by 30%.
  • Christchurch Call: A community of over 130 governments, online service providers, and civil society organisations acting together to eliminate terrorist and violent extremist content online.

Indian steps 

  • Ministry of Electronics and Information Technology's several initiatives have flagged over 9,845 URLs hosting harmful content.
  • IT Rules 2021: It enables tracing the first originator of content on social media, digital news, OTT platforms etc., and removing flagged content within 36 hours.

 

Way forward

  • Algorithmic Audits: Regular algorithm audits should be mandatory to ensure transparency and fairness, similar to European Union's (EU's) Digital Services Act 2023.
  • Accountability measures: Policymakers should clearly define the rules for algorithmic accountability, including penalties for platforms that fail to address the amplification of harmful content.
    • E.g., Germany's Netz law imposes fines on social media platforms for not removing illegal content within 24 hours.
  • Custom-made content moderation: Customized moderation policies (or algorithmic frameworks), tailored to localized contexts, can enhance the effectiveness of interventions to curb radicalisation spread by social media platforms. 
    • E.g., regulators in France partnered with social media companies to enhance their algorithms' ability to detect and moderate extremist content, considering various dialects spoken within the country.
  • Public awareness: Government must conduct public awareness drives to help users identify propaganda and avoid engaging with extremist content.
    • E.g., UK's Online Safety Bill contains provisions for public education initiatives to improve online media literacy.
  • Tags :
  • radicalisation
  • Radicalisation
  • social media algorithms
  • online radicalisation
Download Current Article
Width resize handle
Height resize handle

Search Notes

Filter Notes

No notes yet

Create your first note to get started.

No notes found

Try adjusting your search criteria.

Subscribe for Premium Features