Prediction and explanation in social systems
By Jake M. Hofman, Amit Sharma, Duncan J. Watts. 2017
391 citations recorded by the source corpus.
Subfields: General Social Sciences, Statistical and Nonlinear Physics
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In General Social Sciences
In Statistical and Nonlinear Physics
- M. Dash
- Tharun Mohandoss
- Ritwik Sinha
- Fosca Giannotti
- Dino Pedreschi
- Dhruv Singal
- Sunny Dhamnani
- Arvind Narayanan
Citations in the corpus
- A Survey of Methods for Explaining Black Box Models (2018, background): “results, and a systematic organization and classication of these methodologies is missing. Many questions feed the papers in the literature proposing methodologies for interpreting black box systems [106,34]: What Open The Black Box Survey 3 does it mean that a model is interpretable or transparent?”
- The Society of Algorithms (2021, background): “The coding elite advances computation as the key to unlocking breakthroughs in practically every discipline (Hofman et al. 2017), including sociology (Watts 2014); to transforming every domain of government action (Fourcade & Gordon 2020, O’Reilly 2010); and generally to solving most problems…”
- Leakage and the reproducibility crisis in machine-learning-based science (2023, background): “Besides, publication biases that have been documented in several scientific fields(90,91) can also affect ML-based science.(92,93) [R2] Treat results from ML-based science as tentative.”
- RAPID: Rapid and Precise Interpretable Decision Sets (2019, background): “Both explanation and classification serve important roles, but in more recent years, the role of classification or prediction has been a more dominant theme within computer science research [2].”
- Can Large Language Models Transform Computational Social Science? (2023, neutral): “Explanations are important to social science (Shmueli et al., 2010; Hofman et al., 2017; Yarkoni and Westfall, 2017).”
- Natural language based financial forecasting: a survey (2017, background): “These research designs are also common for other computational social science problems [50].”