Sentiment Analysis in Latvian and Russian: A Survey

[1] K. Ravi and V. Ravi, “A survey on opinion mining and sentiment analysis: Tasks, approaches and applications,” Knowledge-Based Systems, vol. 89, pp. 14–46, 2015. https://doi.org/10.1016/j.knosys.2015.06.01510.1016/j.knosys.2015.06.015Search in Google Scholar

[2] Thomson Reuters, “Thomson Reuters Adds Unique Twitter and News Sentiment Analysis to Thomson Reuters Eikon” [Online]. Available: https://www.thomsonreuters.com/en/press-releases/2014/thomson-reuters-adds-unique-twitter-and-news-sentiment-analysisto-thomson-reuters-eikon.html. [Accessed: Mar.8, 2018].Search in Google Scholar

[3] L. Chen, G. Chen, and F. Wang, “Recommender Systems Based on User Reviews : The State of the Art,” Systematic Reviews 2015, vol. 4, no. 5, 2015.https://doi.org/10.1007/s11257-015-9155-510.1007/s11257-015-9155-5Search in Google Scholar

[4] A. Ceron, “Enlightening the voters: The effectiveness of alternative electoral strategies in the 2013 Italian election monitored through (sentiment) analysis of Twitter posts,” European Consortium for Political Research, pp. 1–25, 2013.Search in Google Scholar

[5] W. Medhat, A. Hassan, and H. Korashy, “Sentiment analysis algorithms and applications: A survey,” Ain Shams Engineering Journal, vol. 5, pp. 1093–1113, 2014. https://doi.org/10.1016/j.asej.2014.04.01110.1016/j.asej.2014.04.011Search in Google Scholar

[6] S. Vohra and J. Teraiya, “Applications and Challenges for Sentiment Analysis : A Survey,” International Journal of Engineering Research and Technology, vol. 2, no. 2, pp. 1–6, 2013.Search in Google Scholar

[7] V. A. Kharde and S. S. Sonawane, “Sentiment Analysis of Twitter Data: A Survey of Techniques,” International Journal of Computer Applications, vol. 139, no. 11, pp. 5–15, 2016. https://doi.org/10.5120/ijca201690862510.5120/ijca2016908625Search in Google Scholar

[8] K. Dashtipour, S. Poria, A. Hussain, E. Cambria, A. Y. A. Hawalah, A. Gelbukh, and Q. Zhou, “Multilingual Sentiment Analysis: State of the Art and Independent Comparison of Techniques,” Cognitive Computation, vol. 8, pp. 757–771, 2016. https://doi.org/10.1007/s12559-016-9415-710.1007/s12559-016-9415-7498162927563360Search in Google Scholar

[9] M. Korayem, K. Aljadda, and D. Crandall, “Sentiment/subjectivity analysis survey for languages other than English,” Social network analysis and mining, vol. 6, no. 1, pp. 1–28, 2016. https://doi.org/10.1007/s13278-016-0381-610.1007/s13278-016-0381-6Search in Google Scholar

[10] “Datasets - Linked Data Models for Emotion and Sentiment Analysis Community Group.” [Online]. Available: https://www.w3.org/community/sentiment/wiki/Datasets. [Accessed: Mar. 8, 2018].Search in Google Scholar

[11] A. Esuli and F. Sebastiani, “SENTIWORDNET: A Publicly Available Lexical Resource for Opinion Mining,” Proceedings of 5th Conference Language Resources and Evaluation, pp. 417–422, 2006.Search in Google Scholar

[12] “MPQA Resources.” [Online]. Available: http://mpqa.cs.pitt.edu/. [Accessed: Mar. 8, 2018].Search in Google Scholar

[13] G. Garkaje, E. Zilgalve, and R. Dargis, “Normalization and Automatized Sentiment Analysis of Contemporary Online Latvian Language,” Frontiers in Artificial Intelligence and Applications, vol. 268, pp. 83–86, 2014. https://doi.org/10.3233/978-1-61499-442-8-83Search in Google Scholar

[14] J. Peisenieks, “Mašīntulkošanas iespējas Twitter sīkziņu sentimenta analīzē,” B. S. thesis, University of Latvia, Latvia, 2014.Search in Google Scholar

[15] J. Peisenieks and R. Skadiņš, “Uses of Machine Translation in the Sentiment Analysis of Tweets,” Frontiers in Artificial Intelligence and Applications, vol. 268, pp. 126–131, 2014.Search in Google Scholar

[16] J. Peisenieks, “Latvian tweet sentiment corpus.” [Online]. Available: https://github.com/FnTm/latvian-tweet-sentiment-corpus. [Accessed: Mar. 10, 2018].Search in Google Scholar

[17] D. Nicmanis, “Sabiedrības attieksmes modelēšana, izmantojot sentimenta analīzi,” B.S. thesis, University of Latvia, Latvia, 2017.Search in Google Scholar

[18] D. Nicmanis, “LV twitter sentiment corpus.” [Online]. Available: https://github.com/nicemanis/LV-twitter-sentiment-corpus. [Accessed: 10-Mar-2018].Search in Google Scholar

[19] K. Gediņš, “Automātiskā teksta emocionālās noskaņas noteikšana latviešu valodā,” B. S. thesis, University of Latvia, Latvia, 2013.Search in Google Scholar

[20] G. Špats and I. Birzniece, “Opinion Mining in Latvian Text Using Semantic Polarity Analysis and Machine Learning Approach,” Complex Systems Informatics and Modeling Quarterly, no. 7, pp. 51–59, 2016. https://doi.org/10.7250/csimq.2016-7.0310.7250/csimq.2016-7.03Search in Google Scholar

[21] “Latvian positive and negative sentiment words.” [Online]. Available: https://github.com/pumpurs/SentimentWordsLV. [Accessed: Mar. 10, 2018].Search in Google Scholar

[22] G. Špats, “Resources for opinion mining for written content classification in Latvian text.” [Online]. Available: https://github.com/gatis/om/tree/master/lexicon. [Accessed: Mar. 10, 2018].Search in Google Scholar

[23] N. Loukachevitch and Y. Rubtsova, “Entity-Oriented Sentiment Analysis of Tweets: Results and Problems Natalia,” Proceedings of the 18th International Conference on Text, Speech, and Dialogue, Lecture Notes in Computer Science, vol. 9302, pp. 551–559, 2015. https://doi.org/10.1007/978-3-319-24033-6_6210.1007/978-3-319-24033-6_62Search in Google Scholar

[24] N. V. Loukachevitch and I. I. Chetviorkin, “Open evaluation of sentiment-analysis systems based on the material of the Russian language,” Scientific and Technical Information Processing, vol. 41, no. 6, pp. 370–376, 2014. https://doi.org/10.3103/S014768821406005710.3103/S0147688214060057Search in Google Scholar

[25] N. S. Sakenovich and A. S. Zharmagambetov, “On One Approach of Solving Sentiment Analysis Task for Kazakh and Russian Languages Using Deep Learning,” Computational Collective Intelligence, Lecture Notes in Computer Science, vol. 10449, pp. 537–545, 2017. https://doi.org/10.1007/978-3-319-45246-3_5110.1007/978-3-319-45246-3_51Search in Google Scholar

[26] E. Tutubalina and S. Nikolenko, “Constructing Aspect-Based Sentiment Lexicons with Topic Modeling,” Proceedings of 5th Conference on Analysis of Images, Social Networks, and Text, vol. 10716, pp. 208–220, 2017. https://doi.org/10.1007/978-3-319-52920-2_2010.1007/978-3-319-52920-2_20Search in Google Scholar

[27] N. V. Loukachevitch, P. D. Blinov, E. V. Kotelnikov, Y. V. Rubtsova, V. V. Ivanov, and E. V. Tutubalina, “SentiRuEval: Testing Objectoriented sentiment analysis systems in Russian,” Computational Linguistics and Intellectual Technologies, vol. 2, no. 14, pp. 3–15, 2015.Search in Google Scholar

[28] G. Shalunts and G. Backfried, “SentiSAIL: Sentiment Analysis in English, German and Russian,” Proceedings of the 11th International Conference on Machine Learning and Data Mining in Pattern Recognition, vol. 9166, 2015. https://doi.org/10.1007/978-3-319-21024-7_610.1007/978-3-319-21024-7_6Search in Google Scholar

[29] R. Galinsky, A. Alekseev, and S. Nikolenko, “Improving Neural Network Models for Natural Language Processing in Russian with Synonyms,” Proceedings of AINL FRUCT 2016 Conference, vol. 3, pp. 45–51, 2016.Search in Google Scholar

[30] V. Bobichev, O. Kanishcheva, and O. Cherednichenko, “Sentiment analysis in the Ukrainian and Russian news,” Proceedings of 2017 IEEE 1st Electrical and Computer Engineering UKRCON 2017, pp. 1050–1055, 2017. https://doi.org/10.1109/UKRCON.2017.810041010.1109/UKRCON.2017.8100410Search in Google Scholar

[31] I. Gulbinskis, “Digitālo tekstu sentimenta analīze,” B. S. thesis, University of Latvia, Latvia, 2010.Search in Google Scholar

[32] “SemTi-Kamols.” [Online]. Available: http://www.semti-kamols.lv/?sadala=220. [Accessed: Mar. 10, 2018].Search in Google Scholar

[33] P. D. Turney, “Thumbs up or thumbs down? Semantic Orientation applied to Unsupervised Classification of Reviews,” Proceedings of the 40th Annual Meeting on Association for Computational Linguistics, no. July, pp. 417–424, 2002.10.3115/1073083.1073153Search in Google Scholar

[34] “Latviešu valodas tekstu korpuss.” [Online]. Available: http://www.korpuss.lv/. [Accessed: Mar. 8, 2018].Search in Google Scholar

[35] P. Paikens, “Latvian morphology module.” [Online]. Available: https://github.com/PeterisP/morphology. [Accessed: Mar. 8, 2018].Search in Google Scholar