Separating facts from fiction: Linguistic models to classify suspicious and trusted news posts on twitter S Volkova, K Shaffer, JY Jang, N Hodas Proceedings of the 55th Annual Meeting of the Association for Computational …, 2017 | 433 | 2017 |
Using social media to predict the future: a systematic literature review L Phillips, C Dowling, K Shaffer, N Hodas, S Volkova arXiv preprint arXiv:1706.06134, 2017 | 102 | 2017 |
Predicting speech acts in MOOC forum posts J Arguello, K Shaffer Proceedings of the International AAAI Conference on Web and Social Media 9 …, 2015 | 76 | 2015 |
Beyond fine tuning: A modular approach to learning on small data A Anderson, K Shaffer, A Yankov, CD Corley, NO Hodas arXiv preprint arXiv:1611.01714, 2016 | 25 | 2016 |
Language Clustering for Multilingual Named Entity Recognition K Shaffer Findings of the Association for Computational Linguistics: EMNLP 2021, 40--45, 2021 | 14 | 2021 |
Intrinsic and extrinsic evaluation of spatiotemporal text representations in Twitter streams L Phillips, K Shaffer, D Arendt, N Hodas, S Volkova Proceedings of the 2nd Workshop on Representation Learning for NLP, 201-210, 2017 | 12 | 2017 |
Beyond fine tuning: Adding capacity to leverage few labels NO Hodas, K Shaffer, A Yankov, CD Corley, A Anderson, W Cheney Proceedings of the 31st Conference on Neural Information Processing Systems, 1-7, 2017 | 2 | 2017 |
Predicting Speech Acts in MOOC Forum Posts Using Conditional Random Fields K Shaffer UNC-Chapel Hill Masters Thesis, 2015 | 1 | 2015 |