Publisher
Springer International Publishing
Reference29 articles.
1. Yang, Y., Liu, Y., Lu, X., Xu, J., Wang, F.: A named entity topic model for news popularity prediction. Knowl.-Based Syst. 208, 106430 (2020)
2. Ambroselli, C., Risch, J., Krestel, R., Loos, A.: Prediction for the newsroom: Which articles will get the most comments? In: Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, New Orleans - Louisiana, vol. 3 (Industry Papers), pp. 193–199 (2018)
3. Davoudi, H., An, A., Edall, G.: Content-based dwell time engagement prediction model for news articles. In: Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Minneapolis, Minnesota, vol. 2 (Industry Papers), pp. 226–233 (2019)
4. Gupta, R.K., Yang, Y.: Predicting and understanding news social popularity with emotional salience features. In: Proceedings of the 27th ACM International Conference on Multimedia, New York, NY, USA, pp. 139–147 (2019)
5. Hamid, A., et al.: Fake news detection in social media using graph neural networks and NLP techniques: a COVID-19 use-case. In: MediaEval. CEUR Workshop Proceedings, vol. 2882 (2020)
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