Abstract
We carried out extensive experiments on the MultiEmo dataset for sentiment analysis with texts in eleven languages. Two adapted versions of the LaBSE deep architecture were confronted against the LASER model. That allowed us to conduct cross-language validation of these language agnostic methods. The achieved results proved that LaBSE embeddings with an additional attention layer within the biLSTM architecture commonly outperformed other methods.
This work was partially supported by the National Science Centre, Poland, project no. 2020/37/B/ST6/03806; by the statutory funds of the Department of Artificial Intelligence, Wroclaw University of Science and Technology; by the European Regional Development Fund as a part of the 2014–2020 Smart Growth Operational Programme, CLARIN - Common Language Resources and Technology Infrastructure, project no. POIR.04.02.00-00C002/19.
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Hemmatian, F., Sohrabi, M.K.: A survey on classification techniques for opinion mining and sentiment analysis. Artif. Intell. Rev. 52(3), 1495–1545 (2017). https://doi.org/10.1007/s10462-017-9599-6
Augustyniak, Ł, Szymański, P., Kajdanowicz, T., Kazienko, P.: Fast and accurate - improving lexicon-based sentiment classification with an ensemble methods. In: Nguyen, N.T., Trawiński, B., Fujita, H., Hong, T.-P. (eds.) ACIIDS 2016. LNCS (LNAI), vol. 9622, pp. 108–116. Springer, Heidelberg (2016). https://doi.org/10.1007/978-3-662-49390-8_10
Bartusiak, R., Augustyniak, L., Kajdanowicz, T., Kazienko, P.: Sentiment analysis for polish using transfer learning approach. In: Second European Network Intelligence Conference 2015, pp. 53–59 (2015)
Miłkowski, P., Gruza, M., Kanclerz, K., Kazienko, P., Grimling, D., Kocon, J.: Personal bias in prediction of emotions elicited by textual opinions. In: ACL-IJCNLP 2021: Student Research Workshop, pp. 248–259. ACL (2021)
Kocoń, J., et al.: Learning personal human biases and representations for subjective tasks in natural language processing. In: ICDM, pp. 1168–1173. IEEE (2021)
Artetxe, M., Schwenk, H.: Massively multilingual sentence embeddings for zero-shot cross-lingual transfer and beyond. Trans. Assoc. Comput. Linguist. 7, 597–610 (2019)
Feng, F., Yang, Y., Cer, D., Arivazhagan, N., Wang, W.: Language-agnostic BERT sentence embedding. arXiv preprint arXiv:2007.01852 (2020)
Miłkowski, P., Gruza, M., Kazienko, P., Szołomicka, J., Woźniak, S., Kocoń, J.: Multiemo: language-agnostic sentiment analysis. In: Proceedings of the 2022 International Conference on Computational Science (ICCS 2022). IEEE (2022)
Kanclerz, K., Miłkowski, P., Kocoń, J.: Cross-lingual deep neural transfer learning in sentiment analysis. Procedia Comput. Sci. 176, 128–137 (2020)
Chen, T., Xu, R., He, Y., Wang, X.: Improving sentiment analysis via sentence type classification using BILSTM-CRF and CNN. Expert Syst. Appl. 72, 221–230 (2017)
Kocoń, J., Miłkowski, P., Zaśko-Zielińska, M.: Multi-level sentiment analysis of Polemo 2.0: extended corpus of multi-domain consumer reviews. In: CoNLL 2019, pp. 980–991 (2019)
Devlin, J., Chang, M.-W., Lee, K., Toutanova, K.: BERT: pre-training of deep bidirectional transformers for language understanding. arXiv preprint arXiv:1810.04805 (2018)
Liu, Y., et al.: Roberta: a robustly optimized BERT pretraining approach. arXiv preprint arXiv:1907.11692 (2019)
Rybak, P., Mroczkowski, R., Tracz, J., Gawlik, I.: Klej: comprehensive benchmark for polish language understanding. arXiv preprint arXiv:2005.00630 (2020)
Calais Guerra, P.H., Veloso, A., Meira Jr., W., Almeida, V.: From bias to opinion: a transfer-learning approach to real-time sentiment analysis. In: ACM SIGKDD’2011, pp. 150–158 (2011)
Pelicon, A., Pranjić, M., Miljković, D., Škrlj, B., Pollak, S.: Zero-shot learning for cross-lingual news sentiment classif. Appl. Sci. 10(17), 5993 (2020)
Zhou, X., Wan, X., Xiao, J.: Attention-based LSTM network for cross-lingual sentiment classification. In: EMNLP’16, pp. 247–256 (2016)
Hripcsak, G., Rothschild, A.S.: Agreement, the f-measure, and reliability in information retrieval. J. Am. Med. Inform. Assoc. 12(3), 296–298 (2005)
Swayamdipta, S., et al.: Dataset cartography: mapping and diagnosing datasets with training dynamics. In: EMNLP 2020, pp. 9275–9293. ACL (2020)
Kocoń, J., Figas, A., Gruza, M., Puchalska, D., Kajdanowicz, T., Kazienko, P.: Offensive, aggressive, and hate speech analysis: from data-centric to human-centered approach. Inf. Process. Manag. 58(5), 102643 (2021)
Kanclerz, K., et al.: Controversy and conformity: from generalized to personalized aggressiveness detection. In: ACL-IJCNLP 2021, pp. 5915–5926. ACL (2021)
Miłkowski, P., Saganowski, S., Gruza, M., Kazienko, P., Piasecki, M., Kocoń, J.: Multitask personalized recognition of emotions evoked by textual content. In: EmotionAware 2022: Sixth International Workshop on Emotion Awareness for Pervasive Computing Beyond Traditional Approaches at PerCom 2022, pp. 347–352, March 2022
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Miłkowski, P., Gruza, M., Kazienko, P., Szołomicka, J., Woźniak, S., Kocoń, J. (2022). Multi-model Analysis of Language-Agnostic Sentiment Classification on MultiEmo Data. In: Nguyen, N.T., Manolopoulos, Y., Chbeir, R., Kozierkiewicz, A., Trawiński, B. (eds) Computational Collective Intelligence. ICCCI 2022. Lecture Notes in Computer Science(), vol 13501. Springer, Cham. https://doi.org/10.1007/978-3-031-16014-1_14
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