Do Stochastic Parrots have Feelings Too? Improving Neural Detection of Synthetic Text via Emotion Recognition

Alan Cowap, Yvette Graham, Jennifer Foster

Abstract
Recent developments in generative AI have shone a spotlight on high-performance synthetic text generation technologies. The now wide availability and ease of use of such models highlights the urgent need to provide equally powerful technologies capable of identifying synthetic text. With this in mind, we draw inspiration from psychological studies which suggest that people can be driven by emotion and encode emotion in the text they compose. We hypothesize that pretrained language models (PLMs) have an affective deficit because they lack such an emotional driver when generating text and consequently may generate synthetic text which has affective incoherence i.e. lacking the kind of emotional coherence present in human-authored text. We subsequently develop an emotionally aware detector by fine-tuning a PLM on emotion. Experiment results indicate that our emotionally-aware detector achieves improvements across a range of synthetic text generators, various sized models, datasets, and domains. Finally, we compare our emotionally-aware synthetic text detector to ChatGPT in the task of identification of its own output and show substantial gains, reinforcing the potential of emotion as a signal to identify synthetic text. Code, models, and datasets are available at https: //github.com/alanagiasi/emoPLMsynth
Anthology ID:
2023.findings-emnlp.665
Volume:
Findings of the Association for Computational Linguistics: EMNLP 2023
Month:
December
Year:
2023
Address:
Singapore
Editors:
Houda Bouamor, Juan Pino, Kalika Bali
Venue:
Findings
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
9928–9946
Language:
URL:
https://aclanthology.org/2023.findings-emnlp.665
DOI:
10.18653/v1/2023.findings-emnlp.665
Bibkey:
Cite (ACL):
Alan Cowap, Yvette Graham, and Jennifer Foster. 2023. Do Stochastic Parrots have Feelings Too? Improving Neural Detection of Synthetic Text via Emotion Recognition. In Findings of the Association for Computational Linguistics: EMNLP 2023, pages 9928–9946, Singapore. Association for Computational Linguistics.
Cite (Informal):
Do Stochastic Parrots have Feelings Too? Improving Neural Detection of Synthetic Text via Emotion Recognition (Cowap et al., Findings 2023)
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PDF:
https://preview.aclanthology.org/nschneid-patch-2/2023.findings-emnlp.665.pdf
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