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Integrating explanation and prediction in computational social science

Citations

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Cited by:

  1. Verhagen, Mark D., 2021. "A Pragmatist's Guide to Using Prediction in the Social Sciences," SocArXiv tjkcy_v1, Center for Open Science.
  2. Filippo Simini & Gianni Barlacchi & Massimilano Luca & Luca Pappalardo, 2021. "A Deep Gravity model for mobility flows generation," Nature Communications, Nature, vol. 12(1), pages 1-13, December.
  3. Malgorzata J. Krawczyk & Mateusz Libirt & Krzysztof Malarz, 2024. "Analysis of scientific cooperation at the international and intercontinental level," Scientometrics, Springer;Akadémiai Kiadó, vol. 129(8), pages 4983-5002, August.
  4. Yan, Jason & Hall, Seventy F. & Sage, Melanie & Du, Yuhao & Joseph, Kenneth, 2024. "A computational social science approach to understanding predictors of Chafee service receipt," Children and Youth Services Review, Elsevier, vol. 158(C).
  5. Ahmed Abbasi & Jeffrey Parsons & Gautam Pant & Olivia R. Liu Sheng & Suprateek Sarker, 2024. "Pathways for Design Research on Artificial Intelligence," Information Systems Research, INFORMS, vol. 35(2), pages 441-459, June.
  6. Rahal, Charles & Verhagen, Mark D. & Kirk, David, 2021. "The Rise of Machine Learning in the Academic Social Sciences," SocArXiv gydve_v1, Center for Open Science.
  7. Ari Hyytinen & Petri Rouvinen & Mika Pajarinen & Joosua Virtanen, 2023. "Ex Ante Predictability of Rapid Growth: A Design Science Approach," Entrepreneurship Theory and Practice, , vol. 47(6), pages 2465-2493, November.
  8. Gary Charness & Brian Jabarian & John List, 2023. "Generation Next: Experimentation with AI," Artefactual Field Experiments 00777, The Field Experiments Website.
  9. Cerqua, Augusto & Letta, Marco, 2022. "Local inequalities of the COVID-19 crisis," Regional Science and Urban Economics, Elsevier, vol. 92(C).
  10. Dario Sansone & Anna Zhu, 2023. "Using Machine Learning to Create an Early Warning System for Welfare Recipients," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 85(5), pages 959-992, October.
  11. Simon Willcock & Javier Martinez-Lopez & Norman Dandy & James M. Bullock, 2021. "High Spatial-Temporal Resolution Data across Large Scales Are Needed to Transform Our Understanding of Ecosystem Services," Land, MDPI, vol. 10(7), pages 1-6, July.
  12. Miguel G. Folgado & Veronica Sanz, 2022. "Exploring the political pulse of a country using data science tools," Journal of Computational Social Science, Springer, vol. 5(1), pages 987-1000, May.
  13. Isabelle Bonhoure & Anna Cigarini & Julián Vicens & Bàrbara Mitats & Josep Perelló, 2023. "Reformulating computational social science with citizen social science: the case of a community-based mental health care research," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-14, December.
  14. Salomi Samsudeen & Mohammed Hasan Ali & C. Chandru Vignesh & M. M. Kamruzzaman & Chander Prakash & Tamizharasi Thirugnanam & J. Alfred Daniel, 2023. "Context-specific discussion of Airbnb usage knowledge graphs for improving private social systems," Journal of Combinatorial Optimization, Springer, vol. 45(2), pages 1-30, March.
  15. Grossmann, Igor & Rotella, Amanda A. & Hutcherson, Cendri & Sharpinskyi, Konstantyn & Varnum, Michael E. W. & Achter, Sebastian K. & Dhami, Mandeep & Guo, Xinqi Evie & Kara-Yakoubian, Mane R. & Mandel, 2023. "Insights into the accuracy of social scientists' forecasts of societal change," Other publications TiSEM c14f4a4a-b105-46b3-90f7-f, Tilburg University, School of Economics and Management.
  16. Oriol J. Bosch & Melanie Revilla, 2022. "When survey science met web tracking: Presenting an error framework for metered data," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 185(S2), pages 408-436, December.
  17. Renáta Németh, 2023. "A scoping review on the use of natural language processing in research on political polarization: trends and research prospects," Journal of Computational Social Science, Springer, vol. 6(1), pages 289-313, April.
  18. Evangelos Katsamakas, 2024. "Business models for the simulation hypothesis," Papers 2404.08991, arXiv.org.
  19. Tavishi Priyam & Tao Ruan & Qin Lv, 2023. "Demographic-Based Public Perception Analysis of Electric Vehicles on Online Social Networks," Sustainability, MDPI, vol. 16(1), pages 1-16, December.
  20. Benjamin W. Domingue & Klint Kanopka & Radhika Kapoor & Steffi Pohl & R. Philip Chalmers & Charles Rahal & Mijke Rhemtulla, 2024. "The InterModel Vigorish as a Lens for Understanding (and Quantifying) the Value of Item Response Models for Dichotomously Coded Items," Psychometrika, Springer;The Psychometric Society, vol. 89(3), pages 1034-1054, September.
  21. Islam, Towhidul & Meade, Nigel & Carson, Richard T. & Louviere, Jordan J. & Wang, Juan, 2022. "The usefulness of socio-demographic variables in predicting purchase decisions: Evidence from machine learning procedures," Journal of Business Research, Elsevier, vol. 151(C), pages 324-338.
  22. Elizabeth Dolan & James Goulding & Harry Marshall & Gavin Smith & Gavin Long & Laila J. Tata, 2023. "Assessing the value of integrating national longitudinal shopping data into respiratory disease forecasting models," Nature Communications, Nature, vol. 14(1), pages 1-19, December.
  23. Nelson P. Rayl & Nitish R. Sinha, 2022. "Integrating Prediction and Attribution to Classify News," Finance and Economics Discussion Series 2022-042, Board of Governors of the Federal Reserve System (U.S.).
  24. Shoshan, Vered & Hazan, Tamir & Plonsky, Ori, 2023. "AS-BEAST: Using machine learning to create an adaptable, scalable, and interpretable behavioral model," OSF Preprints kaeny_v1, Center for Open Science.
  25. Lu Liu & Benjamin F. Jones & Brian Uzzi & Dashun Wang, 2023. "Data, measurement and empirical methods in the science of science," Nature Human Behaviour, Nature, vol. 7(7), pages 1046-1058, July.
  26. Rory Gibb & Felipe J. Colón-González & Phan Trong Lan & Phan Thi Huong & Vu Sinh Nam & Vu Trong Duoc & Do Thai Hung & Nguyễn Thanh Dong & Vien Chinh Chien & Ly Thi Thuy Trang & Do Kien Quoc & Tran Min, 2023. "Interactions between climate change, urban infrastructure and mobility are driving dengue emergence in Vietnam," Nature Communications, Nature, vol. 14(1), pages 1-15, December.
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