Emilio Ferrara
Artificial Intelligence · 2009–2023
A researcher in the Science corpus: 23 papers; trusts 563 researchers and is trusted by 52 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 237 citations into it; #3,867 of 35,345 by trust here, #4,682 by citations
- Statistical and Nonlinear Physics — 187 citations into it; #1,275 of 10,127 by trust here, #1,486 by citations
- Sociology and Political Science — 113 citations into it; #1,125 of 22,756 by trust here, #1,153 by citations
- Information Systems — 103 citations into it; #488 of 8,771 by trust here, #391 by citations
- Safety, Robustness & Interpretability — 70 citations into it
- Natural Language Processing — 65 citations into it
- Safety Research — 55 citations into it; #1,484 of 5,829 by trust here, #2,873 by citations
- Computer Vision and Pattern Recognition — 53 citations into it
Whom Emilio Ferrara trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- Yoshua Bengio
- Ilya Sutskever
- Diederik P. Kingma
- Mark Newman
- Alex Krizhevsky
- Alec Radford
- Yann LeCun
- Kaiming He
- Tomas Mikolov
Who trusts Emilio Ferrara overall
- David M. Beskow
- Kai-Cheng Yang
- Adam Badawy
- Onur Varol
- Kristina Lerman
- Sneha Kudugunta
- Xinyi Zhou
- Filippo Menczer
- Stefano Cresci
- Yan Tao
Papers from Emilio Ferrara's perspective
Ordered by how strongly the researchers Emilio Ferrara trusts endorse each paper. Same corpus, a different order for every researcher.
- 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)
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- ImageNet: A large-scale hierarchical image database
- Gradient-based learning applied to document recognition
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
Their papers
- Graph Embedding Techniques, Applications, and Performance: A Survey (2017) — 1,820 citations
- Disinformation and social bot operations in the run up to the 2017 French presidential election (2017) — 495 citations
- BotOrNot: A System to Evaluate Social Bots (2016) — 923 citations
- The rise of social bots (2014) — 2,064 citations
- Online Human-Bot Interactions: Detection, Estimation, and Characterization (2017) — 1,106 citations
- Measuring Emotional Contagion in Social Media (2015) — 506 citations
- The DARPA Twitter Bot Challenge (2016) — 408 citations
- Deep Neural Networks for Bot Detection (2018) — 509 citations
- Bots increase exposure to negative and inflammatory content in online social systems (2018) — 445 citations
- Style in the Age of Instagram: Predicting Success within the Fashion Industry using Social Media (2015) — 62 citations
- Defining and identifying Sleeping Beauties in science (2015) — 404 citations
- The rise of Jihadist propaganda on social networks (2017) — 65 citations
- Tracking Social Media Discourse About the COVID-19 Pandemic: Development of a Public Coronavirus Twitter Data Set (2020) — 729 citations
- Should ChatGPT be Biased? Challenges and Risks of Bias in Large Language Models (2023) — 394 citations
- Fairness And Bias in Artificial Intelligence: A Brief Survey of Sources, Impacts, And Mitigation Strategies (2023) — 692 citations
- FairFed: Enabling Group Fairness in Federated Learning (2021) — 324 citations
- Embedding Networks with Edge Attributes (2018) — 13 citations
- Dynamics of Content Quality in Collaborative Knowledge Production (2017) — 15 citations
- Evidence of Online Performance Deterioration in User Sessions on Reddit (2016) — 37 citations
- Latent Space Model for Multi-Modal Social Data (2015) — 22 citations