Report NEP-BIG-2022-12-19

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.

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Other reports in NEP-BIG

The following items were announced in this report:

• Purcell, Zoe & Bonnefon, Jean-François, 2022, "Humans Feel Too Special for Machines to Score Their Morals," IAST Working Papers, Institute for Advanced Study in Toulouse (IAST), number 22-146, Nov.
• Shayan Halder, 2022, "FinBERT-LSTM: Deep Learning based stock price prediction using News Sentiment Analysis," Papers, arXiv.org, number 2211.07392, Nov.
• Katarzyna Kopczewska, 2021, "Spatial Machine Learning – New Opportunities for Regional Science," Working Papers, Faculty of Economic Sciences, University of Warsaw, number 2021-16.
• William Barnett & Kun He & Jingtong He, 2022, "Consumption Loan Augmented Divisia Monetary Index and China Monetary Aggregation," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS, University of Kansas, Department of Economics, number 202217, Nov.
• Kakuho Furukawa & Ryohei Hisano & Yukio Minoura & Tomoyuki Yagi, 2022, "A Nowcasting Model of Industrial Production using Alternative Data and Machine Learning Approaches," Bank of Japan Working Paper Series, Bank of Japan, number 22-E-16, Nov.
• , editor2021 & Younus, Ahmed Muayad, 2022, "Effects of Artificial Intelligence, Big Data Analytics, and Business Intelligence on Digital Transformation in UAE Telecommunication Firms," OSF Preprints, Center for Open Science, number 8usrk, Jun, DOI: 10.31219/osf.io/8usrk.
• Petre, Konstantin & Varoutas, Dimitris, 2022, "On the application of Machine Learning in telecommunications forecasting: A comparison," 31st European Regional ITS Conference, Gothenburg 2022: Reining in Digital Platforms? Challenging monopolies, promoting competition and developing regulatory regimes, International Telecommunications Society (ITS), number 265665.
• Zongwu Cai & Ted Juhl, 2020, "The Distribution Of Rolling Regression Estimators," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS, University of Kansas, Department of Economics, number 202218, Aug, revised Dec 2022.
• Duo Qin, 2022, "Redirect the Probability Approach in Econometrics Towards PAC Learning," Working Papers, Department of Economics, SOAS University of London, UK, number 249, Mar.
• Utku U. Acikalin & Tolga Caskurlu & Gerard Hoberg & Gordon M. Phillips, 2022, "Intellectual Property Protection Lost and Competition: An Examination Using Machine Learning," NBER Working Papers, National Bureau of Economic Research, Inc, number 30671, Nov.
• Bonacorsi, Laura & Cerasi, Vittoria & Galfrascoli, Paola & Manera, Matteo, , "ESG Factors and Firms’ Credit Risk," FEEM Working Papers, Fondazione Eni Enrico Mattei (FEEM), number 329521, DOI: 10.22004/ag.econ.329521.
• Langenbucher, Katja, 2022, "Consumer credit in the age of AI: Beyond anti-discrimination law," LawFin Working Paper Series, Goethe University, Center for Advanced Studies on the Foundations of Law and Finance (LawFin), number 42.
• , editor2021 & Younus, Ahmed Muayad, 2022, "The Effect of Artificial Intelligence on Job Performance in China's Small and Medium-Sized Enterprises (SMEs)," OSF Preprints, Center for Open Science, number qg8x7, Jun, DOI: 10.31219/osf.io/qg8x7.
• Dorien Herremans & Kah Wee Low, 2022, "Forecasting Bitcoin volatility spikes from whale transactions and CryptoQuant data using Synthesizer Transformer models," Papers, arXiv.org, number 2211.08281, Oct.
• Bonnefon, Jean-François & Purcell, Zoe, 2022, "Humans Feel Too Special for Machines to Score Their Morals," TSE Working Papers, Toulouse School of Economics (TSE), number 22-1387, Nov.
• Liz Wachs & Colin McMillan & Gale Boyd & Matt Doolin, 2022, "Exploring New Ways to Classify Industries for Energy Analysis and Modeling," Working Papers, Center for Economic Studies, U.S. Census Bureau, number 22-49, Nov.
• Rogelio A. Mancisidor & Kjersti Aas, 2022, "Multimodal Generative Models for Bankruptcy Prediction Using Textual Data," Papers, arXiv.org, number 2211.08405, Oct, revised Feb 2024.
• Matteo Sostero & Songül Tolan, 2022, "Digital skills for all? From computer literacy to AI skills in online job advertisements," JRC Working Papers on Labour, Education and Technology, Joint Research Centre, number 2022-07, Nov.
• Krämer, Jan & Shekhar, Shiva & Hofmann, Janina, 2022, "Regulating Algorithmic Learning in Digital Platform Ecosystems through Data Sharing and Data Siloing: Consequences for Innovation and Welfare," 31st European Regional ITS Conference, Gothenburg 2022: Reining in Digital Platforms? Challenging monopolies, promoting competition and developing regulatory regimes, International Telecommunications Society (ITS), number 265645.
• Wesley Mendes-da-Silva & Israel José dos Santos Felipe & Cristiana Cerqueira Leal & Marcelo Otone Aguiar, 2022, "Tone of Mass Media News Affect Pledge Amounts in Reward Crowdfunding Campaign," NIPE Working Papers, NIPE - Universidade do Minho, number 2/2022.
• Song Li & Jiandong Zhou & Chong MO & Jin LI & Geoffrey K. F. Tso & Yuxing Tian, 2022, "Motif-aware temporal GCN for fraud detection in signed cryptocurrency trust networks," Papers, arXiv.org, number 2211.13123, Nov, revised Mar 2023.
• Leonardo Perotti & Lech A. Grzelak, 2022, "On Pricing of Discrete Asian and Lookback Options under the Heston Model," Papers, arXiv.org, number 2211.03638, Nov, revised Feb 2024.
• Michael P. Leung & Pantelis Loupos, 2022, "Graph Neural Networks for Causal Inference Under Network Confounding," Papers, arXiv.org, number 2211.07823, Nov, revised Dec 2025.
• Kamalbek Karymshakov & Dina Azhgaliyeva & Ranjeeta Mishra & Dastan Aseinov, 2022, "Evaluating COVID-19’s Impact on Firm Performance in the CAREC Region Using Night-Time Light Data: Azerbaijan, Georgia, Kazakhstan, and Mongolia," ADBI Working Papers, Asian Development Bank Institute, number 1332, Jul.
• Niko Hauzenberger & Florian Huber & Karin Klieber & Massimiliano Marcellino, 2022, "Bayesian Neural Networks for Macroeconomic Analysis," Papers, arXiv.org, number 2211.04752, Nov, revised Apr 2024.
• Naudé, Wim, 2022, "The Future Economics of Artificial Intelligence: Mythical Agents, a Singleton and the Dark Forest," IZA Discussion Papers, Institute of Labor Economics (IZA), number 15713, Nov.
• Wei-Chang Yeh & Yu-Hsin Hsieh & Chia-Ling Huang, 2022, "Newly Developed Flexible Grid Trading Model Combined ANN and SSO algorithm," Papers, arXiv.org, number 2211.12839, Sep.
• Zongwu Cai & Pixiong Chen, 2022, "New Online Investor Sentiment and Asset Returns," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS, University of Kansas, Department of Economics, number 202216, Nov, revised Nov 2022.