Joshua A. Tucker
Sociology and Political Science · 2002–2023
A researcher in the Science corpus: 16 papers; trusts 20 researchers and is trusted by 19 researchers here, as inferred from the citation graph.
Subfields
- Sociology and Political Science — 188 citations into it; #2,776 of 22,756 by trust here, #2,161 by citations
- Communication — 66 citations into it; #1,815 of 3,460 by trust here, #559 by citations
- Political Science and International Relations — 66 citations into it; #772 of 4,701 by trust here, #909 by citations
- Cognitive Neuroscience — 46 citations into it
- Economics and Econometrics — 30 citations into it
- Artificial Intelligence — 28 citations into it; #24,600 of 35,345 by trust here, #17,110 by citations
- AI Ethics, Fairness & Society — 11 citations into it
- Statistics and Probability — 11 citations into it
Whom Joshua A. Tucker trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Jan Fidrmuc
- R. Duch
- Seongho Kim
- John Schulman
- K. Poole
- C. Anderson
- Hunt Allcott
- Larry M. Bartels
- David Sanders
- Ashish Vaswani
Who trusts Joshua A. Tucker overall
- Mark A. Kayser
- Marko Klašnja
- Michael Peress
- C. Anderson
- Michael S. Lewis-Beck
- E. Powell
- Marcus Kreuzer
- J. Roozenbeek
- W. Brady
- Xiaobo Lü
Papers from Joshua A. Tucker's perspective
Ordered by how strongly the researchers Joshua A. Tucker trusts endorse each paper. Same corpus, a different order for every researcher.
- Attention is All you Need (Neural Information Processing Systems)
- Language Models are Few-Shot Learners (Neural Information Processing Systems)
- Proximal Policy Optimization Algorithms (arXiv.org)
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Training language models to follow instructions with human feedback (Neural Information Processing Systems)
- Long Short-Term Memory
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
Their papers
- Using social and behavioural science to support COVID-19 pandemic response (2020) — 4,422 citations
- Less than you think: Prevalence and predictors of fake news dissemination on Facebook (2019) — 1,348 citations
- Emotion shapes the diffusion of moralized content in social networks (2017) — 1,037 citations
- Tweeting From Left to Right (2015) — 1,025 citations
- Regional Economic Voting: Russia, Poland, Hungary, Slovakia, and the Czech Republic, 1990–1999 (2006) — 151 citations
- The economy, corruption, and the vote: Evidence from experiments in Sweden and Moldova (2013) — 163 citations
- Political sectarianism in America (2020) — 669 citations
- Large Language Models Can Be Used to Estimate the Ideologies of Politicians in a Zero-Shot Learning Setting (2023) — 28 citations
- Large Language Models Can Be Used to Estimate the Latent Positions of Politicians (2023) — 41 citations
- THE FIRST DECADE OF POST-COMMUNIST ELECTIONS AND VOTING: What Have We Studied, and How Have We Studied It? (2002) — 126 citations
- Political Psychology in the Digital (mis)Information age: A Model of News Belief and Sharing (2020) — 154 citations
- Moderating with the Mob: Evaluating the Efficacy of Real-Time Crowdsourced Fact-Checking (2021)
- Communist socialization and post-communist economic and political attitudes (2014) — 122 citations
- Revisiting Electoral Volatility in Post-Communist Countries: New Data, New Results and New Approaches (2014) — 298 citations
- Pocketbook vs. Sociotropic Corruption Voting (2014) — 124 citations
- Which Parties Can Lead Opinion? Experimental Evidence on Partisan Cue Taking in Multiparty Democracies (2013) — 165 citations