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Report NEP-BIG-2025-05-19
This is the archive for NEP-BIG, a report on new working papers in the area of Big Data. Tom Coupé (Tom Coupe) issued this report. It is usually issued weekly.Subscribe to this report: email, RSS, or Mastodon, or Bluesky.
Other reports in NEP-BIG
The following items were announced in this report:
- Ziqi Li & Zhan Peng, 2025, "Can Moran Eigenvectors Improve Machine Learning of Spatial Data? Insights from Synthetic Data Validation," Papers, arXiv.org, number 2504.12450, Apr.
- Hannes Wallimann & Noah Balthasar, 2025, "Predicting Children's Travel Modes for School Journeys in Switzerland: A Machine Learning Approach Using National Census Data," Papers, arXiv.org, number 2504.09947, Apr.
- Yu Zhang & Zelin Wu & Claudio Tessone, 2025, "Classification-Based Analysis of Price Pattern Differences Between Cryptocurrencies and Stocks," Papers, arXiv.org, number 2504.12771, Apr.
- Kasymkhan Khubiev & Mikhail Semenov, 2025, "Deep Learning Models Meet Financial Data Modalities," Papers, arXiv.org, number 2504.13521, Apr, revised Apr 2025.
- Anton Yang & Jianwei Ai & Costas Arkolakis, 2025, "A Geospatial Approach to Measuring Economic Activity," NBER Working Papers, National Bureau of Economic Research, Inc, number 33619, Mar.
- Koukorinis, Andreas & Peters, Gareth W. & Germano, Guido, 2025, "Generative-discriminative machine learning models for high-frequency financial regime classification," LSE Research Online Documents on Economics, London School of Economics and Political Science, LSE Library, number 128016, Jun.
- Zongxiao Wu & Yizhe Dong & Yaoyiran Li & Baofeng Shi, 2025, "Unleashing the power of text for credit default prediction: Comparing human-written and generative AI-refined texts," Papers, arXiv.org, number 2503.18029, Mar.
- Yu Jeffrey Hu & Jeroen Rombouts & Ines Wilms, 2025, "MLOps Monitoring at Scale for Digital Platforms," Papers, arXiv.org, number 2504.16789, Apr.
- Martina Halouskov'a & v{S}tefan Ly'ocsa, 2025, "Forecasting U.S. equity market volatility with attention and sentiment to the economy," Papers, arXiv.org, number 2503.19767, Mar.
- Achim Ahrens & Victor Chernozhukov & Christian Hansen & Damian Kozbur & Mark Schaffer & Thomas Wiemann, 2025, "An Introduction to Double/Debiased Machine Learning," Papers, arXiv.org, number 2504.08324, Apr, revised Feb 2026.
- Timoth'ee Fabre & Damien Challet, 2025, "Learning the Spoofability of Limit Order Books With Interpretable Probabilistic Neural Networks," Papers, arXiv.org, number 2504.15908, Apr.
- Julian Junyan Wang & Victor Xiaoqi Wang, 2025, "Assessing Consistency and Reproducibility in the Outputs of Large Language Models: Evidence Across Diverse Finance and Accounting Tasks," Papers, arXiv.org, number 2503.16974, Mar, revised Sep 2025.
- Chris Hays & Manish Raghavan, 2025, "Double Machine Learning for Causal Inference under Shared-State Interference," Papers, arXiv.org, number 2504.08836, Apr.
- Tianshi Mu & Pranjal Rawat & John Rust & Chengjun Zhang & Qixuan Zhong, 2025, "Who is More Bayesian: Humans or ChatGPT?," Papers, arXiv.org, number 2504.10636, Apr.
- Zhao, Chuqing & Chen, Yisong, 2025, "LLM-powered Topic Modeling for Discovering Public Mental Health Trends in Social Media," SocArXiv, Center for Open Science, number xbpts_v1, May, DOI: 10.31219/osf.io/xbpts_v1.
- Tianhe Zhang & Suhan Liu & Peng Shi, 2025, "Discrimination-free Insurance Pricing with Privatized Sensitive Attributes," Papers, arXiv.org, number 2504.11775, Apr, revised Jul 2025.
- Julien Pascal, 2025, "Solving economic models with neural networks without backpropagation," BCL working papers, Central Bank of Luxembourg, number 196, Apr.
- Cong William Lin & Wu Zhu, 2025, "Divergent LLM Adoption and Heterogeneous Convergence Paths in Research Writing," Papers, arXiv.org, number 2504.13629, Apr.
- Herbert Dawid & Philipp Harting & Hankui Wang & Zhongli Wang & Jiachen Yi, 2025, "Agentic Workflows for Economic Research: Design and Implementation," Papers, arXiv.org, number 2504.09736, Apr.