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Cited by 6Text and Document Classification TechnologiesTopic ModelingSentiment Analysis and Opinion Mining

ReAct: A Review Comment Dataset for Actionability (and more)

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Choudhary, Gautam, Modani, Natwar, Maurya, Nitish·2021·Lecture Notes in Computer Science
DOI 10.1007/978-3-030-91560-5_24
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Research works printed but not linked: 12

  1. [1]1. Ahmadalinezhad, M., Makrehchi, M.: Detecting agreement and disagreement in political debates. In: International Conference on Social Computing, BehavioralCultural Modeling and Prediction and Behavior Representation in Modeling and Simulation. pp. 54-60. Springer (2018)
  2. [2]2. Cer, D., Yang, Y., Kong, S.y., Hua, N., Limtiaco, N., John, R.S., Constant, N., Guajardo-C´ espedes, M., Yuan, S., Tar, C., et al.: Universal sentence encoder. arXiv preprint arXiv:1803.11175 (2018) · arXiv
  3. [4]4. Dong, L., Wei, F., Duan, Y., Liu, X., Zhou, M., Xu, K.: The automated acquisition of suggestions from tweets. In: Twenty-Seventh AAAI Conference on Artificial Intelligence (2013)
  4. [5]5. Fleiss, J.L.: Measuring nominal scale agreement among many raters. Psychological bulletin 76 (5), 378 (1971)
  5. [7]7. Landis, J.R., Koch, G.G.: The measurement of observer agreement for categorical data. biometrics pp. 159-174 (1977)
  6. [8]8. Liu, Y., Ott, M., Goyal, N., Du, J., Joshi, M., Chen, D., Levy, O., Lewis, M., Zettlemoyer, L., Stoyanov, V.: Roberta: A robustly optimized bert pretraining approach. arXiv preprint arXiv:1907.11692 (2019) · arXiv
  7. [9]9. Meyers, B.S., Munaiah, N., Prud'hommeaux, E., Meneely, A., Wolff, J., Alm, C.O., Murukannaiah, P.: A dataset for identifying actionable feedback in collaborative software development. In: Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers). pp. 126-131 (2018)
  8. [10]10. Mukherjee, A., Liu, B.: Modeling review comments. In: Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). pp. 320-329 (2012)
  9. [12]12. Sanh, V., Debut, L., Chaumond, J., Wolf, T.: Distilbert, a distilled version of bert: smaller, faster, cheaper and lighter. arXiv preprint arXiv:1910.01108 (2019) · arXiv
  10. [13]13. Spasojevic, N., Rao, A.: Identifying actionable messages on social media. In: 2015 IEEE International Conference on Big Data. pp. 2273-2281. IEEE (2015)
  11. [14]14. Tran, D., Valtchanov, A., Ganapathy, K., Feng, R., Slud, E., Goldblum, M., Goldstein, T.: An open review of openreview: A critical analysis of the machine learning conference review process. arXiv preprint arXiv:2010.05137 (2020) · arXiv
  12. [15]15. Zhang, D., Lee, W.S.: Question classification using support vector machines. In: Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval. pp. 26-32 (2003)

Cited by

Sorted by citations

Authors
Choudhary, G., Modani, N., & Maurya, N.
Affiliations
Adobe Systems (United States) (US)
Corresponding author
Choudhary, Gautam
ORCID
Venue
Lecture Notes in Computer Science
Publisher
Springer International Publishing
Published
2021
Pages
336-343
ISSN
  • 0302-9743 (ISSN-L)
  • 1611-3349
DOI
10.1007/978-3-030-91560-5_24
OpenAlex
W4206737057
Cited by
6
References
1
Citations by year
2026: 2 · 2024: 2 · 2023: 2
FWCI
0.46
Type
conference paper
Language
en
Open access
Licence
Locations
  • Lecture notes in computer science (publishedVersion)
  • arXiv (Cornell University) (submittedVersion)
  • arXiv (Cornell University)
Topics
  • Physical Sciences › Computer Science › Artificial Intelligence › Text and Document Classification Technologies
  • Physical Sciences › Computer Science › Artificial Intelligence › Topic Modeling
  • Physical Sciences › Computer Science › Artificial Intelligence › Sentiment Analysis and Opinion Mining
Keywords
reviewer comments, actionability, annotated dataset, crowdsourced annotation, annotation quality, peer review, document evolution

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