Why Can’t Black Women Just Be?: Black Femme Content Creators Navigating Algorithmic Monoliths

Research Background and Issues

• Identified Problems or Challenges:
  Black women, femme-presenting individuals, and non-binary content creators face excessive content moderation and unfair algorithmic recommendations on social media platforms like TikTok, limiting their success. This inequality manifests through the misuse of content moderation tools, racial and gender biases embedded in algorithms, and resulting phenomena such as shadowbanning.

• Significance of the Problem:
  Social media has become a vital platform for many to express creativity and earn income, yet systemic inequality and algorithmic bias deprive marginalized groups of fair opportunities for growth. This not only causes psychological and economic harm to creators but also hinders public appreciation for diverse expressions of racial, gender, and class experiences.

• Research Motivation and Related Work:
  The study employs Black feminist theory and the framework of digital Black feminism to explore the specific impacts of algorithmic bias on content creators. Existing research has focused on racial oppression, algorithmic bias, and identity formation in online communities but has yet to fully examine the unique experiences of specific groups, such as Black women and non-binary creators.

Solution

• Proposed Method or Solution:
  The authors conducted semi-structured interviews to investigate creators' perceptions of platform content moderation and algorithmic operations, aiming to understand how they resist algorithmic oppression through "folk theories." The study proposes redesigning social media experiences centered on "embracing Black joy."

• Innovative Aspects:

  • Emphasizing systemic identification and confrontation of cultural oppression.
  • Analyzing interactions between creators and algorithms through "algorithmic folk theories" and "blindness theories," revealing how algorithms compress marginalized identities into singular, stereotypical narrative frameworks.
  • Introducing care networks centered on Black creators and design recommendations based on serenity and diversity, expanding the understanding of algorithm and platform optimization.

• Implementation Steps and Key Technologies:

  1. Data Collection: The research team interviewed 10 active Black femme-presenting creators on TikTok, focusing on content moderation, shadowbanning, survival strategies, and audience interactions.
  2. Coding and Thematic Analysis: Using Atlas.ti software, the team conducted mixed inductive and deductive coding of interview data to develop key themes of resistance and social interaction.
  3. Theoretical Framework: Combining Black feminist theories (e.g., Patricia Hill Collins' "matrix of oppression") with research on algorithmic folk theories to analyze participants' experiences.

Research Findings

• Specific Findings:

  1. Algorithms compress the personalities and cultures of Black women creators into singular, stereotypical narratives (e.g., "Black Barbie" or "Black Excellence"), making it difficult for their content to reflect diverse identities and personalities.
  2. Creators build and sustain supportive care networks through genuine interactions with followers to resist algorithmic control and class-based content moderation.
  3. The study reinforces the necessity of "digital Black feminism" in designing social media platforms, emphasizing the importance of algorithmic transparency and accountability in addressing algorithmic bias.

• Comparison with Existing Solutions and Advantages:
  Unlike traditional "problem-focused" designs, this study emphasizes deriving design inspiration from the everyday experiences and joy of Black creators, shifting platform optimization towards supporting their diverse expressions and community building.

• Experimental or Evaluation Results:
  Interviews with participants revealed:

  • How external singular perspectives (e.g., mainstream stereotypes about Black individuals) are amplified within platforms through algorithms.
  • When content is excessively moderated or suddenly disappears, creators rely on feedback from followers and fellow creators to identify issues.
  • The persistence and self-expression of content creators despite unfair treatment and psychological burdens.

• Limitations and Future Directions:

  • The study is limited to 10 creators and does not cover the diverse experiences of all Black femme-presenting or non-binary users.
  • It does not delve into a technical audit of TikTok's recommendation algorithm to further validate creators' "folk theories."
  • Future research should expand to include more marginalized groups (e.g., Black LGBTQ+ communities) and conduct independent external audits of algorithms.

Conclusion

This study provides critical insights into how Black femme-presenting individuals resist algorithmic oppression on social media platforms. Using Black feminist theory, the authors propose large-scale platform optimization strategies that prioritize Black creators' joy and diversity. The research calls for platform transparency and accountability while urging society to reconsider how marginalized content creators are treated more equitably.