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Report NEP-BIG-2023-02-06
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:
- Pedro Garcia-del-Barrio & J. James Reade, 2023, "The Impact of Uncertainty on Fan Interest Surrounding Multiple Outcomes in Open European Football Leagues," Economics Discussion Papers, Department of Economics, University of Reading, number em-dp2023-02, Jan.
- Guijin Son & Hanwool Lee & Nahyeon Kang & Moonjeong Hahm, 2023, "Removing Non-Stationary Knowledge From Pre-Trained Language Models for Entity-Level Sentiment Classification in Finance," Papers, arXiv.org, number 2301.03136, Jan, revised Jan 2023.
- Item repec:hal:wpaper:hal-03905325 is not listed on IDEAS anymore
- Thomas Wong & Mauricio Barahona, 2022, "Online learning techniques for prediction of temporal tabular datasets with regime changes," Papers, arXiv.org, number 2301.00790, Dec, revised Aug 2023.
- Gianandrea Lanzara & Sara Lazzaroni & Paolo Masella & Mara P. Squicciarini, 2023, "Do Bishops Matter for Politics? Evidence From Italy," Working Papers, Dipartimento Scienze Economiche, Universita' di Bologna, number wp1179, Jan.
- Rayane Hanifi & Klodiana Istrefi & Adrian Penalver, 2022, "Central Bank Communication of Uncertainty," Working papers, Banque de France, number 898.
- Xiaohong Chen & Yuan Liao & Weichen Wang, 2022, "Inference on Time Series Nonparametric Conditional Moment Restrictions Using General Sieves," Papers, arXiv.org, number 2301.00092, Dec, revised Jan 2023.
- Szabolcs Nagy & Noemi Hajdu, 2022, "Consumer acceptance of the use of artificial intelligence in online shopping: evidence from Hungary," Papers, arXiv.org, number 2301.01277, Dec.
- Huyên Pham & Xavier Warin, 2024, "Mean-field neural networks-based algorithms for McKean-Vlasov control problems ," Working Papers, HAL, number hal-03900810, Mar.
- Fateme Shahabi Nejad & Mohammad Mehdi Ebadzadeh, 2023, "Stock market forecasting using DRAGAN and feature matching," Papers, arXiv.org, number 2301.05693, Jan.
- Yves-C'edric Bauwelinckx & Jan Dhaene & Tim Verdonck & Milan van den Heuvel, 2023, "On the causality-preservation capabilities of generative modelling," Papers, arXiv.org, number 2301.01109, Jan.
- Jiwon Kim & Moon-Ju Kang & KangHun Lee & HyungJun Moon & Bo-Kwan Jeon, 2023, "Deep Reinforcement Learning for Asset Allocation: Reward Clipping," Papers, arXiv.org, number 2301.05300, Jan.
- Tanja Aue & Adam Jatowt & Michael Farber, 2022, "Predicting Companies' ESG Ratings from News Articles Using Multivariate Timeseries Analysis," Papers, arXiv.org, number 2212.11765, Nov.
- Eugenia Go & Kentaro Nakajima & Yasuyuki Sawada & Kiyoshi Taniguchi, 2023, "Satellite-Based Vehicle Flow Data to Assess Local Economic Activities," CIRJE F-Series, CIRJE, Faculty of Economics, University of Tokyo, number CIRJE-F-1209, Jan.
- Scoggins, Bermond & Robertson, Matthew P., 2023, "Measuring Transparency in the Social Sciences: Political Science and International Relations," I4R Discussion Paper Series, The Institute for Replication (I4R), number 14.
- Stéphane Goutte & Viet Hoang Le & Fei Liu & Hans-Jörg Mettenheim, Von, 2023, "Esg Investing: A Sentiment Analysis Approach," Working Papers, HAL, number halshs-03917335, Jan.
- Stéphane Goutte & Viet Hoang Le & Fei Liu & Hans-Jörg Mettenheim, Von, 2023, "Deep Learning And Technical Analysis In Cryptocurrency Market," Working Papers, HAL, number halshs-03917333, Jan.