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Stance detection, as the task of determining the viewpoint of a social media post towards a target as 'favor' or 'against', has been understudied in the challenging yet realistic scenario where there is limited labeled data for a certain target.
Roberta: A robustly optimized bert pretraining approach
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Birds of a feather: Homophily in social networks
McPherson, M., Smith-Lovin, L., Cook, J.M., 2001 · 2001
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Exploiting cloze questions for few shot text classification and natural language inference
Schick, T., Schütze, H., 2020 · 2001
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Stance classification of ideological debates: Data, models, features, and constraints, in: Proceedings of the sixth international joint conference on natural language processing, pp. 1348–1356
Hasan, K.S., Ng, V., 2013 · 2013
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Sentiment analysis algorithms and applications: A survey
Medhat, W., Hassan, A., Korashy, H., 2014 · 2014
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Joint models of disagreement and stance in online debate, in: Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing (Volume 1: Long Papers), pp. 116–125
Sridhar, D., Foulds, J., Huang, B., Getoor, L., Walker, M., 2015 · 2015
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Stance detection with bidirectional conditional encoding
Augenstein, I., Rocktäschel, T., Vlachos, A., Bontcheva, K., 2016 · 2016
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Semeval-2016 task 6: Detecting stance in tweets, in: Proceedings of the 10th international workshop on semantic evaluation (SemEval-2016), pp. 31–41
Mohammad, S., Kiritchenko, S., Sobhani, P., Zhu, X., Cherry, C., 2016 · 2016
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Zubiaga, A., Kochkina, E., Liakata, M., Procter, R., Lukasik, M., 2016 · 2016
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Stance classification with target-specific neural attention networks, International Joint Conferences on Artificial Intelligence
Du, J., Xu, R., He, Y., Gui, L., 2017 · 2017
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A simple but tough-to-beat baseline for the fake news challenge stance detection task
Riedel, B., Augenstein, I., Spithourakis, G.P., Riedel, S., 2017 · 2017
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Fake news detection on social media: A data mining perspective
Shu, K., Sliva, A., Wang, S., Tang, J., Liu, H., 2017 · 2017
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A dataset for multi-target stance detection, in: Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 2, Short Papers, pp. 551–557
Sobhani, P., Inkpen, D., Zhu, X., 2017 · 2017
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A review of natural language processing techniques for opinion mining systems
Sun, S., Luo, C., Chen, J., 2017 · 2017
Cited alongside, same era.
Graph embedding techniques, applications, and performance: A survey
Goyal, P., Ferrara, E., 2018 · 2018
Cited alongside, same era.
A retrospective analysis of the fake news challenge stance detection task
Hanselowski, A., PVS, A., Schiller, B., Caspelherr, F., Chaudhuri, D., Meyer, C.M., Gurevych, I., 2018 · 2018
Cited alongside, same era.
Automatic stance detection using end-to-end memory networks
Mohtarami, M., Baly, R., Glass, J., Nakov, P., Màrquez, L., Moschitti, A., 2018 · 2018
Cited alongside, same era.
Stance detection with hierarchical attention network, in: Proceedings of the 27th international conference on computational linguistics, pp. 2399–2409
Sun, Q., Wang, Z., Zhu, Q., Zhou, G., 2018 · 2018
Interpreting bert-based stance classification: a case study about the brazilian covid vaccination, in: Anais do XXXVI Simpósio Brasileiro de Bancos de Dados, SBC. pp. 73–84
Sáenz, C.A.C., Becker, K., 2021 · 2021
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Capturing stance dynamics in social media: open challenges and research directions
Alkhalifa, R., Zubiaga, A., 2022 · 2022
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Community detection for access-control decisions: Analysing the role of homophily and information diffusion in online social networks
Ferreyra, N.E.D., Hecking, T., Aïmeur, E., Heisel, M., Hoppe, H.U., 2022 · 2022
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Infusing knowledge from wikipedia to enhance stance detection
He, Z., Mokhberian, N., Lerman, K., 2022 · 2022
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Few-shot stance detection via target-aware prompt distillation, in: Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 837–847
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Cited alongside, same era.
Cross-target stance classification with self-attention networks
Xu, C., Paris, C., Nepal, S., Sparks, R., 2018 · 2018
Cited alongside, same era.
A longitudinal assessment of the persistence of twitter datasets
Zubiaga, A., 2018 · 2018
Cited alongside, same era.
Zubiaga, A., Wang, B., Liakata, M., Procter, R., 2019 · 2019
Cited alongside, same era.
Stander: an expert-annotated dataset for news stance detection and evidence retrieval, Association for Computational Linguistics
Conforti, C., Berndt, J., Pilehvar, M.T., Giannitsarou, C., Toxvaerd, F., Collier, N., 2020 · 2020
Cited alongside, same era.
Stance detection: A survey
Küçük, D., Can, F., 2020 · 2020
Cited alongside, same era.
Stance detection on social media: State of the art and trends
AlDayel, A., Magdy, W., 2021 · 2021
Cited alongside, same era.
Opinions are made to be changed: Temporally adaptive stance classification, in: Proceedings of the 2021 workshop on open challenges in online social networks, pp. 27–32
Alkhalifa, R., Kochkina, E., Zubiaga, A., 2021 · 2021
Cited alongside, same era.
Jiang, Y., Gao, J., Shen, H., Cheng, X., 2022 · 2022
Later among the works it cites.
Jointcl: a joint contrastive learning framework for zero-shot stance detection, in: Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), Association for Computational Linguistics. pp. 81–91
Liang, B., Zhu, Q., Li, X., Yang, M., Gui, L., He, Y., Xu, R., 2022 · 2022
Later among the works it cites.
Few-shot learning for cross-target stance detection by aggregating multimodal embeddings
Khiabani, P.J., Zubiaga, A., 2023 · 2023
Later among the works it cites.
Evaluating the generalisability of neural rumour verification models
Kochkina, E., Hossain, T., Logan IV, R.L., Arana-Catania, M., Procter, R., Zubiaga, A., Singh, S., He, Y., Liakata, M., 2023 · 2023
Later among the works it cites.
Zero-shot and few-shot stance detection on varied topics via conditional generation, in: Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), pp. 1491–1499
Wen, H., Hauptmann, A.G., 2023 · 2023
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C-stance: A large dataset for chinese zero-shot stance detection, in: Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pp. 13369–13385
Zhao, C., Li, Y., Caragea, C., 2023 · 2023
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Correction: Enhancing stance detection through sequential weighted multi-task learning
Alturayeif, N., Luqman, H., Ahmed, M., 2024 · 2024
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Mitigating biases of large language models in stance detection with calibration
Li, A., Zhao, J., Liang, B., Gui, L., Wang, H., Zeng, X., Wong, K.F., Xu, R., 2024 · 2024
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Natural language processing in the era of large language models
Zubiaga, A., 2024 · 2024
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