A Literature Review of Video-Sharing Platform Research in HCI

Literature Title

A Literature Review of Video-Sharing Platform Research in HCI

Literature Information

• Domain: Human-Computer Interaction (HCI), Research Review on Video-Sharing Platforms
• Keywords: Literature review, video, video sharing, YouTube, TikTok, Twitch, video interaction, user community

Research Background and Issues

• Identified Issues or Challenges:

  1. Video-sharing platforms (VSPs) like YouTube, TikTok, and Twitch have experienced rapid growth and attracted a large user base in recent years. However, the HCI field lacks a comprehensive review of research topics, methods, and key findings related to video sharing.
  2. Existing literature often focuses on individual platforms or treats video sharing as part of social media, overlooking the distinct characteristics of VSPs.
  3. VSPs are not only content communities but also involve complex user and social dynamics, driven by platform algorithms and services.

• Significance:
  VSPs serve as core interaction mediums between content creators and audiences, featuring unique social activities, technological characteristics, and business models. Their study holds broad significance in HCI, advancing the understanding of design and social interactions.

• Research Motivation and Related Work:

  1. Current HCI research often targets individual topics or components without forming a holistic connection, necessitating a systematic review to establish a comprehensive framework.
  2. Past studies on social networking platforms primarily focus on behavior, privacy, and data analysis, while the interaction characteristics of VSPs remain underexplored.
  3. This paper reviews HCI literature from 2012 to 2022, aiming to fill gaps in the field.

Solution

• Method or Solution: The authors conducted a scoping review of 106 HCI research papers related to VSPs, categorizing and identifying six core research themes and five components of video sharing, exploring research methods, and proposing future directions.

• Innovations:

  1. Proposed a systematic five-component framework, including Creator, Viewer, Video, Community, and Platform.
  2. Applied grounded theory analysis methods, using open coding, axial coding, and selective coding to introduce new research theme classifications.

• Implementation Steps and Key Techniques:

  • Literature Search: Identified 18 major HCI conferences and journals, designed keywords, and conducted searches via Google Scholar.
  • Data Filtering and Coding: Used programmatic filtering and manual review mechanisms, ultimately selecting 106 papers for analysis.
  • Grounded Theory Application: Analyzed textual content and classified it to generate a multidimensional theoretical framework.
  • Research Method Classification: Summarized various research methods, including qualitative observation, interviews, surveys, big data analysis, user research, and evaluation.

Research Findings

• Specific Findings:

  1. Six Core Research Themes:

     • Online communities and internet subcultures: Focus on specific communities or interest groups.
     • Social participation and relationships: Study interactions and social activities between creators and audiences.
     • New video interaction systems and technologies: Design new tools or enhance existing video functionalities.
     • Interaction with platforms: Analyze how users interact with platform algorithms and features.
     • Video as design material: Extract design knowledge from diverse video data.
     • Video as machine learning datasets: Use video content as training data.

  2. Five-Component Framework:

     • Creator: Motivations, identity management, etc., of creators.
     • Viewer: Interaction behaviors and experiences of viewers.
     • Video: Analysis of video content and interaction methods.
     • Platform: Impact of platform algorithms and service design.
     • Community: Dynamics and social norms within communities.

• Advantages Over Existing Solutions:

  • The comprehensive review framework helps integrate fragmented research content.
  • Provides clear research directions and emphasizes the importance of cross-platform studies in the field.

• Experimental or Evaluation Results:

  • Themes extracted through grounded theory analysis demonstrate the diversity and key areas of video-sharing research in HCI.
  • Big data analysis reveals relationships and trends involving algorithms, interaction behaviors, and content.

• Limitations and Future Directions:

  • Limitations: The paper does not address platform-specific regional or cultural differences; it pays limited attention to non-video social applications.
  • Future Directions:
    • Comparative cross-platform studies to explore unique features of different platforms.
    • Focus on the user experiences and inclusive design for marginalized groups.
    • Increased attention to algorithm fairness, privacy, and authenticity protection research.
    • In-depth exploration of user motivations and behaviors related to community interaction design.