Meta-Identity and Digital Platforms: The Influence of Algorithmic Decision-Making on Social and Personal Identities

Herison Ferreira, Allan

The rise of digital platforms has reshaped how individuals construct and perceive social and personal identities. From a sociological perspective, meta-identity refers to the categorizable and indexable information that individuals provide to digital platforms. This data is processed on a large scale to set parameters that influence algorithms, often shaped by the unclear intentions of decision-makers. The impact of such algorithmic decision-making is profound, creating identity frameworks users might not fully control or understand.

This proposal presents findings from the analysis of over 400 content creators who produced approximately 100 amateur films in a laboratory environment for platforms. By comparing how authors, their peers, and the public label these works with the categorizations generated by platforms like YouTube, the study examines divergences that may occurs between human and algorithmic understandings. It explores how these differences shape identity, influence public visibility, reinforce stereotypes, and limit the diversity of perspectives available to creators and audiences.

The study offers a critical perspective on the broader impact of algorithmic decision-making and highlights the need for greater transparency in how platforms manage data. It advocates for policies to ensure fairer, more inclusive digital environments where content creators and users can maintain control over their identities and the narratives shaped by platforms.

Topics for Discussion:

Analyze the role of meta-identity in shaping social and personal identities on digital platforms.
Present findings from over 400 content creators and 100 amateur films, examining how platforms categorize user identities.
Explore the implications of algorithmic decision-making on the diversity of perspectives and identity construction.
Discuss the importance of transparency, user control, and policy-making to mitigate the impacts of algorithmic identity formation.