Stefano Cresci
Sociology and Political Science · 2015–2020
A researcher in the Science corpus: 5 papers; trusts 30 researchers and is trusted by 2 researchers here, as inferred from the citation graph.
Subfields
- Sociology and Political Science — 52 citations into it; #21,625 of 22,756 by trust here, #16,211 by citations
- Information Systems — 44 citations into it; #6,650 of 8,771 by trust here, #4,012 by citations
- Artificial Intelligence — 37 citations into it; #32,589 of 35,345 by trust here, #25,040 by citations
- Statistical and Nonlinear Physics — 20 citations into it
- Signal Processing — 18 citations into it; #7,298 of 7,572 by trust here, #5,570 by citations
- Computer Networks and Communications — 16 citations into it
- Natural Language Processing — 15 citations into it
- Safety, Robustness & Interpretability — 8 citations into it
Whom Stefano Cresci trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Chao Yang
- Eric R. Ziegel
- Emilio Ferrara
- Rowan Zellers
- Chih-Jen Lin
- Onur Varol
- Stijn van Dongen
- K. Gwet
- Kyumin Lee
- Robert Chandler Harkreader
Who trusts Stefano Cresci overall
- David M. Beskow
- Sneha Kudugunta
- Jacopo Castellini
- Emilio Ferrara
- Wonseok (Eric) Jang
- Octavio Loyola-González
- Kai-Cheng Yang
- Valentina Poggioni
Papers from Stefano Cresci's perspective
Ordered by how strongly the researchers Stefano Cresci trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
- GENERATIVE ADVERSARIAL NETS
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
Their papers
- The Paradigm-Shift of Social Spambots: Evidence, Theories, and Tools for the Arms Race (2017) — 522 citations
- Measuring objective and subjective well-being: dimensions and data sources (2020) — 312 citations
- A Survey on Computational Propaganda Detection (2020) — 216 citations
- A decade of social bot detection (2020) — 320 citations
- Fame for sale: Efficient detection of fake Twitter followers (2015) — 460 citations