Can Few Lines of Code Change Society ? Beyond fack-checking and moderation : how recommender systems toxifies social networking sites

by   David Chavalarias, et al.

As the last few years have seen an increase in online hostility and polarization both, we need to move beyond the fack-checking reflex or the praise for better moderation on social networking sites (SNS) and investigate their impact on social structures and social cohesion. In particular, the role of recommender systems deployed at large scale by digital platforms such as Facebook or Twitter has been overlooked. This paper draws on the literature on cognitive science, digital media, and opinion dynamics to propose a faithful replica of the entanglement between recommender systems, opinion dynamics and users' cognitive biais on SNSs like Twitter that is calibrated over a large scale longitudinal database of tweets from political activists. This model makes it possible to compare the consequences of various recommendation algorithms on the social fabric and to quantify their interaction with some major cognitive bias. In particular, we demonstrate that the recommender systems that seek to solely maximize users' engagement necessarily lead to an overexposure of users to negative content (up to 300% for some of them), a phenomenon called algorithmic negativity bias, to a polarization of the opinion landscape, and to a concentration of social power in the hands of the most toxic users. The latter are more than twice as numerous in the top 1% of the most influential users than in the overall population. Overall, our findings highlight the urgency to identify harmful implementations of recommender systems to individuals and society in order better regulate their deployment on systemic SNSs.


Explicit User Manipulation in Reinforcement Learning Based Recommender Systems

Recommender systems are highly prevalent in the modern world due to thei...

Recommender Systems and Algorithmic Hate

Despite increasing reliance on personalization in digital platforms, man...

Privacy-Preserving Recommender Systems Challenge on Twitter's Home Timeline

Recommender systems constitute the core engine of most social network pl...

Mysterious and Manipulative Black Boxes: A Qualitative Analysis of Perceptions on Recommender Systems

Recommender systems are used to provide relevant suggestions on various ...

Cognitive Analysis of Security Threats on Social Networking Services: Slovakia in need of stronger action

This short paper examines some of the ongoing research at the UMB Data a...

The closed loop between opinion formation and personalised recommendations

In social media, recommender systems are responsible for directing the u...

Auditing Recommender Systems – Putting the DSA into practice with a risk-scenario-based approach

Today's online platforms rely heavily on recommendation systems to serve...

Please sign up or login with your details

Forgot password? Click here to reset