Report NEP-BIG-2020-12-21

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.

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Other reports in NEP-BIG

The following items were announced in this report:

• Bo Cowgill & Fabrizio Dell'Acqua & Samuel Deng & Daniel Hsu & Nakul Verma & Augustin Chaintreau, 2020, "Biased Programmers? Or Biased Data? A Field Experiment in Operationalizing AI Ethics," Papers, arXiv.org, number 2012.02394, Dec.
• Bojing Feng & Wenfang Xue & Bindang Xue & Zeyu Liu, 2020, "Every Corporation Owns Its Image: Corporate Credit Ratings via Convolutional Neural Networks," Papers, arXiv.org, number 2012.03744, Dec.
• Lara Marie Demajo & Vince Vella & Alexiei Dingli, 2020, "Explainable AI for Interpretable Credit Scoring," Papers, arXiv.org, number 2012.03749, Dec.
• Itf, 2019, "New Directions for Data-Driven Transport Safety," International Transport Forum Policy Papers, OECD Publishing, number 83, May, DOI: 10.1787/2b2f71bc-en.
• Louis Abraham, 2020, "Competition analysis on the over-the-counter credit default swap market," Papers, arXiv.org, number 2012.01883, Dec.
• John Aoga & Juhee Bae & Stefanija Veljanoska & Siegfried Nijssen & Pierre Schaus, 2020, "Impact of weather factors on migration intention using machine learning algorithms," Papers, arXiv.org, number 2012.02794, Dec.
• Burka, Dávid & Puppe, Clemens & Szepesváry, László & Tasnádi, Attila, 2020, "Voting: A machine learning approach," Working Paper Series in Economics, Karlsruhe Institute of Technology (KIT), Department of Economics and Management, number 145, DOI: 10.5445/IR/1000127945.
• Hugo Bodory & Martin Huber & Luk'av{s} Laff'ers, 2020, "Evaluating (weighted) dynamic treatment effects by double machine learning," Papers, arXiv.org, number 2012.00370, Dec, revised Jun 2021.
• Avela, Aleksi & Lehmus, Markku, 2020, "It’s in the News: Developing a Real Time Index for Economic Uncertainty Based on Finnish News Titles," ETLA Working Papers, The Research Institute of the Finnish Economy, number 84, Dec.
• Kleinebrahm, Max & Torriti, Jacopo & McKenna, Russell & Ardone, Armin & Fichtner, Wolf, 2020, "Using neural networks to model long-term dependencies in occupancy behavior," Working Paper Series in Production and Energy, Karlsruhe Institute of Technology (KIT), Institute for Industrial Production (IIP), number 49, DOI: 10.5445/IR/1000126271.
• Sergio A. Pernice, 2020, "Serie de Machine Learning Análisis de Componentes Principales (PCA)," CEMA Working Papers: Serie Documentos de Trabajo., Universidad del CEMA, number 770, Dec.
• Agnese Carella & Federica Ciocchetta & Valentina Michelangeli & Federico Maria Signoretti, 2020, "What can we learn about mortgage supply from online data?," Questioni di Economia e Finanza (Occasional Papers), Bank of Italy, Economic Research and International Relations Area, number 583, Nov.
• Olson, Alex & Calderon-Figueroa, Fernando & Bidian, Olimpia & Silver, Daniel & Sanner, Scott, 2020, "Reading the city through its neighbourhoods: Deep text embeddings of Yelp reviews as a basis for determining similarity and change," SocArXiv, Center for Open Science, number 8jbvg, Dec, DOI: 10.31219/osf.io/8jbvg.
• Peter Cook & Felicity O'Neill, 2020, "Artificial Intelligence in Agribusiness is Growing in Emerging Markets," World Bank Publications - Reports, The World Bank Group, number 34304, May.
• Matteo Marrazzo & Nicola Orsini, 2020, "Stata/SQL/Python integration to emulate prospective cohort studies from big register data," Nordic and Baltic Stata Users' Group Meeting 2019, Stata Users Group, number 12, Aug.
• Müller-Peters, Horst (Ed.) & Schmidt, Jan-Philipp (Ed.) & Völler, Michaele (Ed.), 2020, "Revolutionieren Big Data und KI die Versicherungswirtschaft? 24. Kölner Versicherungssymposium am 14. November 2019," Forschung am ivwKöln, Technische Hochschule Köln – University of Applied Sciences, Institute for Insurance Studies, number 7/2020.
• Aksoy, Cevat Giray & Poutvaara, Panu & Schikora, Felicitas, 2020, "First Time Around: Local Conditions and Multi-dimensional Integration of Refugees," SocArXiv, Center for Open Science, number nsr8q, Nov, DOI: 10.31219/osf.io/nsr8q.
• Cevat Giray Aksoy & Panu Poutvaara & Felicitas Schikora, 2020, "First Time Around: Local Conditions and Multi-Dimensional Integration of Refugees," CESifo Working Paper Series, CESifo, number 8747.
• Aksoy, Cevat Giray & Poutvaara, Panu & Schikora, Felicitas, 2020, "First Time around: Local Conditions and Multi-Dimensional Integration of Refugees," IZA Discussion Papers, IZA Network @ LISER, number 13914, Nov.
• Markus Eyting, 2020, "A Random Forest a Day Keeps the Doctor Away," Working Papers, Gutenberg School of Management and Economics, Johannes Gutenberg-Universität Mainz, number 2026, Dec.
• Michal Balcerak & Thomas Schmelzer, 2020, "Constructing trading strategy ensembles by classifying market states," Papers, arXiv.org, number 2012.03078, Dec.
• Rahul Goel & Lucas Javier Ford & Maksym Obrizan & Rajesh Sharma, 2020, "COVID-19 and the stock market: evidence from Twitter," Papers, arXiv.org, number 2011.08717, Nov.
• Ahmed Nauraiz Rana, 2020, "Leveraging Big Data to Advance Gender Equality," World Bank Publications - Reports, The World Bank Group, number 34308, Jun.
• Zhiguo He & Jing Huang & Jidong Zhou, 2020, "Open Banking: Credit Market Competition When Borrowers Own the Data," NBER Working Papers, National Bureau of Economic Research, Inc, number 28118, Nov.