#PoetsOfInstagram: Navigating The Practices And Challenges Of Novice Poets On Instagram

Document Title

#PoetsOfInstagram: Navigating The Practices And Challenges Of Novice Poets On Instagram

Document Information

• Subject Area: Research on online creative communities, particularly the response of poetry communities to algorithmic influence
• Keywords: Social media, online communities, algorithmic awareness, creative labor, user-generated content (UGC)

Research Background and Questions

• Issues and Challenges:

  • How does Instagram, primarily a platform for visual content, serve text-based art forms such as poetry?
  • How do novice creators in the poetry community understand and navigate the impact of recommendation algorithms on their creation and dissemination?
  • A research gap exists in the in-depth study of how non-commercial novice creators are constrained by algorithm-driven platforms.

• Significance:

  • Poetry, as an art form, has become increasingly marginalized in modern society, while Instagram’s poetry community offers opportunities for its revival.
  • Studying this community helps to understand how UGC and platform technological logic support or limit novice and diverse creative expressions.

• Research Motivation and Related Work:

  • Existing studies mainly focus on the online practices of professional creators, lacking sufficient exploration of the labor and practices of non-professional novice creators.
  • The activities of novice creators reveal how algorithmic decisions influence the diversity of UGC and may restrict truly unique forms of individual expression.

Solution

• Methodology:

  • Conduct qualitative analysis using in-depth semi-structured interviews (N=15) and content from Instagram poetry community posts (N=240).
  • Employ grounded theory-inspired analytical methods, focusing on deconstructing the motivations, values, and practices of the creative community while uncovering the potential impact of algorithms on community behavior.

• Innovations:

  • Introduced the concept of “Algorithmically Mediated Creative Labor” (AMCL), defining the additional labor creators must undertake to adapt to algorithmic logic.
  • Focused on non-monetized creators, contrasting their creative labor with more commercially driven practices on the platform.

• Implementation Details:

  • Data Collection: Filter Instagram content using popular hashtags and recruit novice creators with fewer than 5,000 followers for interviews.
  • Data Analysis: Conduct multiple rounds of open and focused coding, combining interview insights with content analysis to extract themes.
  • Key Techniques: Highlight the community’s unique participatory culture and original practices, while integrating users’ algorithmic perceptions to understand their impact.

Research Outcomes

• Specific Findings:

  • Articulated the values of the Instagram poetry community, such as emphasizing originality in creation, participatory sharing, and opposition to plagiarism.
  • Highlighted the tensions between algorithms and creative practices, particularly how visual-first recommendation systems limit the dissemination of text-based content.

• Advantages Over Existing Solutions:

  • In studying creator-algorithm interactions, this research focuses more on the specific needs of non-commercial creators rather than merely discussing the monetization logic of platformized content creation.
  • Emphasizes community-centered recommendation systems, proposing more human-centered mechanisms compared to existing commercially driven approaches.

• Experiments and Evaluations:

  • Content Analysis: Results showed that most poetry posts (<500 characters) had unrelated visual and textual content, indicating creators’ compromises to align with algorithmic preferences.
  • Interview Results: Creators expressed widespread disappointment with algorithms, with most believing platform support depended on their willingness to pursue monetization.

• Limitations and Future Directions:

  • Limitations: Data collection was limited to English-speaking creators, and practices may differ for creators from other linguistic backgrounds.
  • Future Directions:
    • Study other non-monetized creative communities, such as DIY artists or grassroots movement organizations.
    • Further explore the adaptability of “Algorithmically Mediated Creative Labor” in the context of evolving algorithms.
    • Examine creators’ responses to rapid technological changes, particularly those with limited resources and education.