تجزیه و تحلیل احساسات در سطح ویژگی محصول و مبتنی بر جنسیت کاربران

Abdous, M., & He, W. (2011). Using text mining to uncover students’ technologyrelated problems in live video streaming. British Journal of Educational Technology, 40(5), 40-49.

Ansari, M., Aziz, M., Siddiqui, M., Mehra, H., & Singh, K. (2020). Analysis of Political Sentiment Orientations on Twitter. Procedia Computer Science, 167, 1821-1828.

Basari, A. S., Hussin, B., Ananta, G. B., & Zeniarja, J. (2013). Opinion Mining of Movie Review using Hybrid Method of Support Vector Machine and Particle Swarm Optimization. Procedia Engineering, 53, 453–462.

Belkaroui, R., & Faiz, R. (2015). Towards events tweet contextualization using social in uence model and users conversations. In Proceedings of the 5th International Conference on Web Intelligence, Mining and Semantics, page3.ACM.

Cambria, E., Schuller, B., Xia, Y., & Havasi, C. (2013). New avenues in opinion mining and sentiment analysis. IEEE Intelligent Systems, 28(2), 15-21. doi:0.1109/MIS.2013.30.

Global Web Index. (2020). Social H3 2020 report. Global Web Index: https://www.globalwebindex.com/reports/social

He, W., Shen, J., Li, Y., Akula, V., Yan, G., & Tao, R. (2015). Gaining competitive intelligence from social media data: Evidence from two largest retail chains in the world. Industrial Management & Data Systems, 115(9), 1622-1636.

He, W., Zha, S., & Li, L. (2013). Social media competitive analysis and text mining: A case study in the pizza industry. International Journal of Information Management, 33, 464-472.

Hu, M., & Liu, B. (2004). Mining opinion features in customer review. In processing of 19th National Conference on Artifical intelligence, AAAI Press, (. 755-760).

Hung, C., & Lin, H. K. (2013). Using Objective Words in SentiWordNet to Improve Word-of-Mouth Sentiment Classification. IEEE Intelligent Systems, 28(2), 47-54.

Hutto, C. J., & Gilbert, E. (2014). VADER: A Parsimonious Rule-Based Model for Sentiment Analysis of Social Media Text. AAAI Publications, Eighth International AAAI Conference on Weblogs and Social Media.

Ibrahim, N., & Wang, X. (2019). Decoding the sentiment dynamics of online retailing customers: Time series analysis of social media. Computers in Human Behavior(96), 32-45.

Li, Z. C., Zhang, M., MA, S. P., Zhou, B., & Sun, Y. (2009). Automatic extraction for product feature words from comments on the web. In: G.G. Lee (Ed.), Information Retrieval Technology, Springer-Verlag Berlin, Berlin, 112-123.

Liang, P. W., & Bi-Ru, D. (2013). Opinion Mining on Social Media Data. 2013 IEEE 14th International Conference on Mobile Data Management. Milan, Italy: IEEE. doi:10.1109/MDM.2013.73

Martinez, I., Valencia-Garcia, R., & Garcia-Sanchez, F. (2011). ntology-Guided Approach to Feature-Based Opinion Mining. Natural Language Processing and Information Systems, 193-200.

Mikula, M., & Machova, K. (2015). Classification of opinions in conversational content. IEEE 13th International Symposium on Applied Machine Intelligence and Informatics, (. 22-24).

Othman, R., Belkaroui, R., & Faiz, R. (2017). Extracting Product Features for Opinion Mining Using Public Conversations in Twitter. International Conference on Knowledge Based and Intelligent Information and Engineering Systems, KES2017, Procedia Computer Science 112 (2017), (. 927-935).

Pang, B., & Lee, L. (2002). Thumbs up ? Sentiment Classification using Machine Learning Techniques. In ACL-02 conference on Empirical methods in natural language processing, (79-86). doi:10.3115/1118693.1118704.

Pearson, T., & Wegener, R. (2013). Big data: the organizational challenge. September 11, 2013، www.bain.com/publications/articles/big_data_the_organizational_challenge.aspx

Piryani, R., Madhavi, D., & Singh, V. K. (2016). Analytical mapping of opinion mining and sentiment analysis research during 2000–2015. Information Processing and Management, 53(1), 122-150.

Vinodhini, G., & Chandrasekaran, R. M. (2013). Sentiment Mining Using SVM-Based Hybrid Classification Model. Computational Intelligence, Cyber Security and Computational Models (. 155-162). New Delhi: Springer. doi:10.1007/978-81-322-1680-3_18

Wang, H., Gao, S., Yin, P., & Nga-Kwok, J. (2017). Competitiveness analysis through comparative relattion mining: evidence from restaurant` online review. Industrial Management & Data Systems, 117(4), 672-687.

Ye, Q., Zhang, Z., & Law, R. (2009). Sentiment Classification of Online Review to Travel destinations by supervised machine learning approaches. Expert Systems with Applications, 36(3), 267-307.

Zhang, L., Biu, B., Lim, S. H., & O'Brien-Strain , E. (2010). Extracting and ranking product features in opinion documents. In Proceesings of the 23rd International Conference on Computational Linguistics: Posters, COLING' 10, Stroudsburg, PA, USA, (1462–1470).

Zhuang, L., Jing, F., & Zhu, X. (2006). Movie review mining and summarization. In processing of the ACM International Conference on Information and Knowledge Management (CIKM-2006), (. 43-50).

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‌ ‌استناد به این مقاله: محمدی، شهریار، ناظمی، اسلام. (1400). تجزیه‌وتحلیل احساسات در سطح ویژگی محصول و مبتنی بر جنسیت کاربران، مطالعات مدیریت کسب وکار هوشمند، 10(37)، 267-296.

DOI: 10.22054/IMS.2021.52110.1723

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