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Using application programming interfaces for Web 2.0 user research: the case of networked public expectancies and feedback preferences on YouTube

Cédric Courtois (UGent) and Peter Mechant (UGent)
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Abstract
In our presentation, we discuss a recent research project on the video sharing platform YouTube. Every day, more than 150,000 new videos are added, most of them user-generated. However, little is known about for whom YouTube users upload these videos. In a first phase, we performed 20 in depth face-to-face interviews. This led to the induction of two dimensions that yield three distinct networked public types. Also, we found preliminary evidence of uploaders using feedback to infer whether their expected public actually watches a video. In a second phase, YouTube's Application Programming Interface (API; a gateway to interact with the platform) was used to select uploaders to participate in an online questionnaire. In this survey, we measured the expectancies of the networked public types to watch their most recent video. Also, the importance they attribute to various types of feedback was measured. As such, the earlier findings were qualitatively validated on two separate samples: a general sample (N = 450) and a specific sample of teenagers (N = 242). In a third phase, we again used the API to log the received on-platform feedback (views, comments and rates) at three distinct moments. By means of a latent growth analysis, we revealed that teenage uploaders' public expectancies fairly correspond with the receipt of feedback that is deemed indicative for the public types they upload for. In sum, our research incorporates the analysis of both conventional self-report data and public platform data (API). As such, we were able to match user perceptions with reliable system data.

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Chicago
Courtois, Cédric, and Peter Mechant. 2011. “Using Application Programming Interfaces for Web 2.0 User Research: The Case of Networked Public Expectancies and Feedback Preferences on YouTube.” In New Challenges and Methodological Innovations in European Media Audience Research, Meeting Abstracts.
APA
Courtois, C., & Mechant, P. (2011). Using application programming interfaces for Web 2.0 user research: the case of networked public expectancies and feedback preferences on YouTube. New challenges and methodological innovations in European Media Audience Research, Meeting Abstracts. Presented at the COST Action ISO906 : New challenges and methodological innovations in European Media Audience Research.
Vancouver
1.
Courtois C, Mechant P. Using application programming interfaces for Web 2.0 user research: the case of networked public expectancies and feedback preferences on YouTube. New challenges and methodological innovations in European Media Audience Research, Meeting Abstracts. 2011.
MLA
Courtois, Cédric, and Peter Mechant. “Using Application Programming Interfaces for Web 2.0 User Research: The Case of Networked Public Expectancies and Feedback Preferences on YouTube.” New Challenges and Methodological Innovations in European Media Audience Research, Meeting Abstracts. 2011. Print.
@inproceedings{1207402,
  abstract     = {In our presentation, we discuss a recent research project on the video sharing platform YouTube. Every day, more than 150,000 new videos are added, most of them user-generated. However, little is known about for whom YouTube users upload these videos. In a first phase, we performed 20 in depth face-to-face interviews. This led to the induction of two dimensions that yield three distinct networked public types. Also, we found preliminary evidence of uploaders using feedback to infer whether their expected public actually watches a video. In a second phase, YouTube's Application Programming Interface (API; a gateway to interact with the platform) was used to select uploaders to participate in an online questionnaire. In this survey, we measured the expectancies of the networked public types to watch their most recent video. Also, the importance they attribute to various types of feedback was measured. As such, the earlier findings were qualitatively validated on two separate samples: a general sample (N = 450) and a specific sample of teenagers (N = 242). In a third phase, we again used the API to log the received on-platform feedback (views, comments and rates) at three distinct moments. By means of a latent growth analysis, we revealed that teenage uploaders' public expectancies fairly correspond with the receipt of feedback that is deemed indicative for the public types they upload for. In sum, our research incorporates the analysis of both conventional self-report data and public platform data (API). As such, we were able to match user perceptions with reliable system data.},
  author       = {Courtois, C{\'e}dric and Mechant, Peter},
  booktitle    = {New challenges and methodological innovations in European Media Audience Research, Meeting Abstracts},
  language     = {eng},
  location     = {Zagreb, Croatia},
  title        = {Using application programming interfaces for Web 2.0 user research: the case of networked public expectancies and feedback preferences on YouTube},
  year         = {2011},
}