Report NEP-BIG-2021-08-23

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:

• Emily Aiken & Suzanne Bellue & Dean Karlan & Christopher R. Udry & Joshua Blumenstock, 2021, "Machine Learning and Mobile Phone Data Can Improve the Targeting of Humanitarian Assistance," NBER Working Papers, National Bureau of Economic Research, Inc, number 29070, Jul.
• Mathilde Gerardin & Martial Ranvier, 2021, "Enrichment of the Banque de France s monthly business survey: lessons from textual analysis of business leaders comments," Working papers, Banque de France, number 821.
• Anjali Adukia & Alex Eble & Emileigh Harrison & Hakizumwami Birali Runesha & Teodora Szasz, 2021, "What We Teach About Race and Gender: Representation in Images and Text of Children’s Books," NBER Working Papers, National Bureau of Economic Research, Inc, number 29123, Aug.
• Subhadeep Mukhopadhyay, 2021, "InfoGram and Admissible Machine Learning," Papers, arXiv.org, number 2108.07380, Aug, revised Aug 2021.
• Tugce Karatas & Ali Hirsa, 2021, "Two-Stage Sector Rotation Methodology Using Machine Learning and Deep Learning Techniques," Papers, arXiv.org, number 2108.02838, Aug.
• Liang Zeng & Lei Wang & Hui Niu & Ruchen Zhang & Ling Wang & Jian Li, 2021, "Trade When Opportunity Comes: Price Movement Forecasting via Locality-Aware Attention and Iterative Refinement Labeling," Papers, arXiv.org, number 2107.11972, Jul, revised Jul 2024.
• Pumplun, Luisa & Fecho, Mariska & Wahl, Nihal & Peters, Felix & Buxmann, Peter, 2021, "Adoption of Machine Learning Systems for Medical Diagnostics in Clinics: A Qualitative Interview Study," Publications of Darmstadt Technical University, Institute for Business Studies (BWL), Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL), number 127993, Oct.
• A. K. M. Amanat Ullah & Fahim Imtiaz & Miftah Uddin Md Ihsan & Md. Golam Rabiul Alam & Mahbub Majumdar, 2021, "Combining Machine Learning Classifiers for Stock Trading with Effective Feature Extraction," Papers, arXiv.org, number 2107.13148, Jul, revised Aug 2023.
• Huseyin Gurkan & Francis de Véricourt, 2020, "Contracting, pricing, and data collection under the AI flywheel effect," ESMT Research Working Papers, ESMT European School of Management and Technology, number ESMT-20-01_R3, Mar, revised 17 Aug 2021.
• Steve J. Bickley & Benno Torgler, 2021, "Cognitive Architectures for Artificial Intelligence Ethics," CREMA Working Paper Series, Center for Research in Economics, Management and the Arts (CREMA), number 2021-27, Aug.
• Allen Hu & Song Ma, 2021, "Persuading Investors: A Video-Based Study," NBER Working Papers, National Bureau of Economic Research, Inc, number 29048, Jul.
• Alexander Trott & Sunil Srinivasa & Douwe van der Wal & Sebastien Haneuse & Stephan Zheng, 2021, "Building a Foundation for Data-Driven, Interpretable, and Robust Policy Design using the AI Economist," Papers, arXiv.org, number 2108.02904, Aug.
• Hamza Saad & Nagendra Nagarur & Abdulrahman Shamsan, 2021, "Analysis of Data Mining Process for Improvement of Production Quality in Industrial Sector," Papers, arXiv.org, number 2108.07615, Aug.
• Kee, Shaira Limson & Garganera, John Patrick & Maravilla, Nicholle Mae Amor & Garganera, Wilbert & Fermin, Jamie Ledesma & AlDahoul, Nouar & Karim, Hezerul Abdul & Tan, Myles Joshua, 2021, "Riding the Tide Toward the Digital Era: The Imminent Alliance of AI and Mental Health in the Philippines," OSF Preprints, Center for Open Science, number 3wg5p, Aug, DOI: 10.31219/osf.io/3wg5p.
• Cédric Vernier & Denis Loeillet & Rallou Thomopoulos & Catherine Macombe, 2021, "Adoption of ICTs in Agri-Food Logistics: Potential and Limitations for Supply Chain Sustainability," Post-Print, HAL, number hal-03280502, Jun, DOI: 10.3390/su13126702.
• Muhammed Taher Al-Mudafer & Benjamin Avanzi & Greg Taylor & Bernard Wong, 2021, "Stochastic loss reserving with mixture density neural networks," Papers, arXiv.org, number 2108.07924, Aug.
• Charlson, G., 2021, "Third-Degree Price Discrimination in the Age of Big Data," Cambridge Working Papers in Economics, Faculty of Economics, University of Cambridge, number 2159, Aug.
• Rui (Aruhan) Shi, 2021, "Learning from Zero: How to Make Consumption-Saving Decisions in a Stochastic Environment with an AI Algorithm," CESifo Working Paper Series, CESifo, number 9255.
• Raquel Fernández & Sahar Parsa, 2021, "Gay Politics Goes Mainstream: Democrats, Republicans, and Same-Sex Relationships," NBER Working Papers, National Bureau of Economic Research, Inc, number 29062, Jul.
• Aaltonen, Aleksi Ville & Alaimo, Cristina & Kallinikos, Jannis, 2021, "The making of data commodities: data analytics as an embedded process," LSE Research Online Documents on Economics, London School of Economics and Political Science, LSE Library, number 110296, Aug.
• Geoff Boeing & Max Besbris & David Wachsmuth & Jake Wegmann, 2021, "Tilted Platforms: Rental Housing Technology and the Rise of Urban Big Data Oligopolies," Papers, arXiv.org, number 2108.08229, Aug.
• Stephen Coussens & Jann Spiess, 2021, "Improving Inference from Simple Instruments through Compliance Estimation," Papers, arXiv.org, number 2108.03726, Aug.
• Angelo M. Fasolo & Flávia M. Graminho & Saulo B. Bastos, 2021, "Seeing the Forest for the Trees: using hLDA models to evaluate communication in Banco Central do Brasil," Working Papers Series, Central Bank of Brazil, Research Department, number 555, Aug.

Report NEP-BIG-2021-08-23

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: