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Report NEP-BIG-2022-10-03
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:
- Asei ITO & Jaehwan LIM & Hongyong ZHANG, 2022, "Catching the Political Leader's Signals: Economic policy uncertainty and firm investment in China," Discussion papers, Research Institute of Economy, Trade and Industry (RIETI), number 22081, Aug.
- Shafuillah Qureshi & Ba Chu & Fanny S. Demers & Michel Demers, 2022, "Using Natural Language Processing to Measure COVID-19-Induced Economic Policy Uncertainty for Canada and the US," Carleton Economic Papers, Carleton University, Department of Economics, number 22-01, Jan.
- Jeaneth Machicao & Imed Riadh Farah & Leonardo Meneguzzi & Corrêa Pedro Luiz Pizzigatti & Alison Specht & Romain David & Gérard Subsol & Danton Ferreira Vellenich & Rodolphe Devillers & Shelley Stall , 2022, "Mitigation Strategies to Improve Reproducibility of Poverty Estimations From Remote Sensing Images Using Deep Learning," Post-Print, HAL, number hal-03761874, DOI: 10.1029/2022ea002379.
- Phillip Heiler, 2022, "Heterogeneous Treatment Effect Bounds under Sample Selection with an Application to the Effects of Social Media on Political Polarization," Papers, arXiv.org, number 2209.04329, Sep, revised Jul 2024.
- Long, Vicky & Bjuggren, Per-Olof, 2022, "Working Paper No. 355: The artificial intelligence (AI) data access regime: what are the factors affecting the access and sharing of industrial AI data?," Ratio Working Papers, The Ratio Institute, number 355, May.
- Elda Xhumari & Suela Maxhelaku & Endrit Xhina, 2022, "A review of Knowledge Graph and Graph Neural Network application," Proceedings of Economics and Finance Conferences, International Institute of Social and Economic Sciences, number 13615626, Jul.
- Federico Fioravanti & Iyad Rahwan & Fernando Tohmé, 2022, "Properties of Aggregation Operators Relevant for Ethical Decision Making in Artificial Intelligence," Working Papers, Red Nacional de Investigadores en Economía (RedNIE), number 177, Sep.
- Arnoud V. den Boer & Janusz M. Meylahn & Maarten Pieter Schinkel, 2022, "Artificial Collusion: Examining Supracompetitive Pricing by Q-learning Algorithms," Tinbergen Institute Discussion Papers, Tinbergen Institute, number 22-067/VII, Sep.
- Oscar Calvo-Gonz'alez & Axel Eizmendi & Germ'an Reyes, 2022, "The Shifting Attention of Political Leaders: Evidence from Two Centuries of Presidential Speeches," Papers, arXiv.org, number 2209.00540, Sep, revised Jun 2023.
- Barbaglia, Luca & Frattarolo, Lorenzo & Onorante, Luca & Pericoli, Filippo Maria & Ratto, Marco & Tiozzo Pezzoli, Luca, 2022, "Testing big data in a big crisis: Nowcasting under COVID-19," JRC Working Papers in Economics and Finance, Joint Research Centre, European Commission, number 2022-06, Aug.
- Béatrice BOULU-RESHEF & Catherine BRUNEAU & Maxime NICOLAS & Thomas RENAULT, 2022, "An Experimental Analysis of Investor Sentiment," LEO Working Papers / DR LEO, Orleans Economics Laboratory / Laboratoire d'Economie d'Orleans (LEO), University of Orleans, number 2940.
- Mike Kraehenbuehl & Joerg Osterrieder, 2022, "The Efficient Market Hypothesis for Bitcoin in the context of neural networks," Papers, arXiv.org, number 2208.07254, Jun.
- Danijel Jevtic & Romain Deleze & Joerg Osterrieder, 2022, "AI for trading strategies," Papers, arXiv.org, number 2208.07168, Jun.
- Leonardo de Assis Santos & Leonardo Marques, 2022, "Big data analytics for supply chain risk management: research opportunities at process crossroads," Post-Print, HAL, number hal-03766121, DOI: 10.1108/BPMJ-01-2022-0012.
- Leogrande, Angelo & Costantiello, Alberto & Laureti, Lucio, 2022, "The Impact of New Doctorate Graduates on Innovation Systems in Europe," MPRA Paper, University Library of Munich, Germany, number 114452, Sep.
- Henrika Langen, 2022, "The Impact of the #MeToo Movement on Language at Court -- A text-based causal inference approach," Papers, arXiv.org, number 2209.00409, Sep, revised Sep 2023.
- Om Mane & Saravanakumar kandasamy, 2022, "Stock Market Prediction using Natural Language Processing -- A Survey," Papers, arXiv.org, number 2208.13564, Aug.