ChatGPT as a Commenter to the News: Can LLMs Generate Human-Like Opinions?

Author:

Tseng Rayden,Verberne SuzanORCID,van der Putten PeterORCID

Publisher

Springer Nature Switzerland

Reference17 articles.

1. Adelani, D.I., Mai, H., Fang, F., Nguyen, H.H. Yamagishi, J., Echizen, I.: Generating sentiment-preserving fake online reviews using neural language models and their human- and machine-based detection. In: Advanced Information Networking and Applications, pp. 1341–1354 (2020)

2. Brown, T., et al.: Language models are few-shot learners. In: Advances in Neural Information Processing Systems, vol. 33, pp. 1877–1901 (2020)

3. Chiu, K.-L., Collins, A., Alexander, R.: Detecting hate speech with GPT-3. arXiv preprint arXiv:2103.12407 (2021)

4. Delobelle, P., Winters, T., Berendt, B.: RobBERT: a Dutch RoBERTa-based language model. In: Findings of the Association for Computational Linguistics: EMNLP 2020, pp. 3255–3265. Association for Computational Linguistics, November 2020

5. Devlin, J., Chang, M.-W., Lee, K., Toutanova, K.: BERT: pre-training of deep bidirectional transformers for language understanding. In: Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers), pp. 4171–4186 (2019)

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