If you use word shift graphs in your work, please cite the following paper:
Gallagher, R. J., Frank, M. R., Mitchell, Lewis, Schwartz, A. J., Reagan, A. J., Danforth, C. M., Dodds, P. S. (2021). Generalized Word Shift Graphs: A Method for Visualizing and Explaining Pairwise Comparisons Between Texts. EPJ Data Science, 10(4).
Sentiment Analysis Citations
The Shifterator package includes several pre-compiled sentiment lexicons. If you use any of the following lexicons, please cite the appropriate sources.
If you use the English LabMT sentiment lexicon, cite the following papers:
Dodds, P. S., Harris, K. D., Kloumann, I. M., Bliss, C. A., & Danforth, C. M. (2011). Temporal Patterns of Happiness and Information in a Global Social Network: Hedonometrics and Twitter. PLoS ONE, 6(12).
If you use any of the non-Engish LabMT sentiment lexicons, cite the following paper:
Dodds, P. S., Clark, E. M., Desu, S., Frank, M. R., Reagan, A. J., Williams, J. R., Mitchell, L., Harris, K. D., Kloumann, I. M., Bagrow, J. P., & Megerdoomian, K. (2015). Human Language Reveals a Universal Positivity Bias. Proceedings of the National Academy of Sciences, 112(8), 2389-2394.
If you use any of the NRC VAD sentiment lexicons, cite the following paper:
Obtaining Reliable Human Ratings of Valence, Arousal, and Dominance for 20,000 English Words. Saif M. Mohammad. In Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics, Melbourne, Australia, July 2018.
If you use any of the NRC emotion intensity lexicons, cite the following paper:
Word Affect Intensities. Saif M. Mohammad. In Proceedings of the 11th Edition of the Language Resources and Evaluation Conference (LREC-2018), May 2018, Miyazaki, Japan.
Details of the NRC sentiment lexicon constructions are available here.
If you use any of the SocialSent sentiment lexicons, cite the following paper:
Hamilton, W. L., Clark, K., Leskovec, J., & Jurafsky, D. (2016). Inducing Domain-Specific Sentiment Lexicons from Unlabeled Corpora. In Proceedings of the Conference on Empirical Methods in Natural Language Processing. Vol. 2016, p. 595.
Details of the SocialSent sentiment lexicon constructions are available here.