Construct · 1 fields · 2 citations

algorithmic folk theories: a standalone construct

One name. One construct. A landmark on the map.

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algorithmicfolk theories1 CONSTRUCTAlgorithmic folk theoriesDEVITO · FOLK THEORIES

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Human-computer interaction / social computing

The intuitive, non-expert explanations users build for how an algorithmic feed works

Michael A. DeVito, Darren Gergle, and Jeremy Birnholtz named the construct in 2017 at CHI, in a study of the #RIPTwitter backlash, defining algorithmic folk theories as the intuitive, non-expert causal explanations users construct to make sense of, and act on, how a platform's algorithmic feed selects and ranks content. These theories need not be technically correct; what matters is that people use them to decide how to post, when to trust the feed, and whether to resist a change, so a folk theory becomes a basis for behavior and collective reaction. DeVito and colleagues (2018) developed the account further, theorizing how such folk theories form and what that means for how researchers study self-presentation online. The construct is distinctive because it treats users' lay reasoning about opaque systems as a structured, consequential object of study in its own right, and it sits in the human-computer interaction and social-computing tradition.[1][2]

Unit
One user's causal theory of how an algorithmic feed selects and ranks content
Recovery means
Not applicable
Measured by
Elicited through interviews and analysis of user discourse about how a feed works, coded into the causal theories people hold and the actions they take on them

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Nearby constructs

algorithmic imaginary1 fields · 2 citationsanchor · a standalone constructuser resistance4 names · 4 citationsjangle · one construct, many modelsbacklash2 fields · 2 citationsjingle · one word, two constructs

References

  1. DeVito, M. A., Gergle, D., & Birnholtz, J. (2017). "Algorithms ruin everything": #RIPTwitter, folk theories, and resistance to algorithmic change in social media. Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems, 3163-3174. https://doi.org/10.1145/3025453.3025659
  2. DeVito, M. A., Birnholtz, J., Hancock, J. T., French, M., & Liu, S. (2018). How people form folk theories of social media feeds and what it means for how we study self-presentation. Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems. https://doi.org/10.1145/3173574.3173694

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