Bit by bit: social research in the digital age
By Sandra González-Bailón. 2019
299 citations recorded by the source corpus.
In his 1963 book Informal Sociology, William Bruce Cameron wrote the often-misattributed quote “not everything that can be counted counts, and not everything that counts can be counted”. With this ...
Subfields: Communication
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Communication
- Alexandra Olteanu
- Fernando Diaz
- Carlos Castillo
- Emre Kıcıman
- Jeffery S. McMullen
- Claudia Wagner
- Muhammad Imran
- Gabriella Kazai
Citations in the corpus
- Social Data: Biases, Methodological Pitfalls, and Ethical Boundaries (2019, background): “Platform affordances are often driven by business considerations and interests (Van Dijck, 2013a; Salganik, 2017), and influenced by the politics, assumptions, and interests of those designing and building these platforms (Van Dijck, 2013a; West et al., 2019).”
- Editorial: Enhancing quantitative theory-testing entrepreneurship research (2019, background): “There is often a valid trade-off between causal evidence and evaluating theoretical models holistically; for example, testing models with multiple dependent variables or models with many predictors simultaneously (Salganik, 2017).”
- "Unsex me here": Revisiting Sexism Detection Using Psychological Scales and Adversarial Samples (2020, background): “d to train the machine learning models. This impedes assessing which aspects of sexism are contained in the training data. Consequently, this raises the issues of construct validity (Sen et al. 2019; Salganik 2017). Finally, there have been no detailed investigations into models capturing spurious a”
- Out of One, Many: Using Language Models to Simulate Human Samples (2022, background): “We acknowledge these dangers, and both join with and strongly endorse the work of others in pushing for a clear standardof ethics for their use in researchanddeployment (Ross 2012; Salganik 2017).”
- Text and Causal Inference: A Review of Using Text to Remove Confounding from Causal Estimates (2020, background): “However, with the proliferation of the web and social media, social research now includes large-scale observational data that would be challenging to obtain using surveys (Salganik, 2017).”