Franciska de Jong
Artificial Intelligence · 2012–2016
A researcher in the Science corpus: 4 papers; trusts 28 researchers and is trusted by 7 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 63 citations into it; #27,053 of 35,345 by trust here, #14,438 by citations
- Natural Language Processing — 27 citations into it; #4,061 of 5,688 by trust here, #4,793 by citations
- Human-Computer Interaction — 20 citations into it
- Language and Linguistics — 19 citations into it
- Communication — 15 citations into it
- Information Systems — 12 citations into it
- Social Psychology — 11 citations into it; #10,545 of 15,694 by trust here, #7,199 by citations
- Literature and Literary Theory — 10 citations into it
Whom Franciska de Jong trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Dong Nguyen
- Jacob Eisenstein
- Penelope Eckert
- Cristian Danescu-Niculescu-Mizil
- James W. Pennebaker
- Moshe Koppel
- Katja Filippova
- Shlomo Engelson Argamon
- David Bamman
- Sali A. Tagliamonte
Who trusts Franciska de Jong overall
Papers from Franciska de Jong's perspective
Ordered by how strongly the researchers Franciska de Jong trusts endorse each paper. Same corpus, a different order for every researcher.
- Efficient Estimation of Word Representations in Vector Space
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Attention is All you Need (Neural Information Processing Systems)
- Latent Dirichlet Allocation
- Long Short-Term Memory
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
- LIBLINEAR: A Library for Large Linear Classification
- Gradient-based learning applied to document recognition
Their papers
- Computational Sociolinguistics: A Survey (2016) — 205 citations
- Improving Cyberbullying Detection with User Context (2013) — 396 citations
- Why Gender and Age Prediction from Tweets is Hard: Lessons from a Crowdsourcing Experiment (2014) — 135 citations
- Improved cyberbullying detection using gender information (2012) — 205 citations