[1] F. Abbasi, A. Khadivar and M. Yazdinejad, "A grouping hotel recommender system based on deep learning and sentiment analysis," Journal of Information Technology Management, vol. 11, no. 2, pp. 59-78, 2019. https://doi.org/10.22059/jitm.2019.289271.2402
[2] K. S. Al-Omoush and N. S. Alghusin, "Exploring the organizational and social drivers of social media analytics: the domino effect in Fintech innovation," International Journal of Accounting & Information Management, vol. 33, no. 2, pp. 407-424, 2025, https://doi.org/10.1108/IJAIM-02-2024-0076
[3] S. H. Janjua, G. F. Siddiqui, M. A. Sindhu and U. Rashid, "Multi-level aspect based sentiment classification of Twitter data: using hybrid approach in deep learning," PeerJ Computer Science, vol. 7, p. e433, 2021. https://doi.org/10.7717/peerj-cs.433
[4] K. Suresh Kumar, S. Nidamanuri, P. B. Acharjee, S. Arulraj, P. Vellingiri, and G. Sasetharan, "Contemporary Social Media And Iot Based Pandemic Control; An Analytical Approach," Migration Letters, vol. 21, no. S5, pp. 531-538, 2024. https://migrationletters.com/index.php/ml/article/vie w/7732/5008
[5] D. C. Nguyen et al., "6G Internet of Things: A comprehensive survey," IEEE Internet of Things Journal, vol. 9, no. 1, pp. 359-383, 2021, https://doi.org/10.1109/JIOT.2021.3103320
[6] K. Sandhu, A. Dayanandan and S. Kuntluru, "Fintech innovation for financial inclusion: can India make it?," International Journal of Accounting & Information Management, no. ahead-of-print, 2023, https://doi.org/10.1108/IJAIM-07-2023-0168
[7] F. Abbasi and A. Khadivar, "Collaborative filtering recommendation system through sentiment analysis," Turkish Journal of Computer and Mathematics Education, vol. 12, no. 14, pp. 1843-1853, 2021. https://ssrn.com/abstract=4176463
[8] M. Birjali, M. Kasri and A. Beni-Hssane, "A comprehensive survey on sentiment analysis: Approaches, challenges and trends," Knowledge-Based Systems, vol. 226, p. 107134, 2021, https://doi.org/10.1016/j.knosys.2021.107134
[9] Z. Wang, D. Huang, J. Cui, X. Zhang, S.-B. Ho and E. Cambria, "A review of Chinese sentiment analysis: subjects, methods, and trends," Artificial Intelligence Review, vol. 58, no. 3, p. 75, 2025. https://doi.org/10.1007/s10462-024-10988-9
[10] Z. Wang, Z. Hu, S. B. Ho, E. Cambria and A. H. Tan, "MiMuSA—mimicking human language understanding for fine-grained multi-class sentiment analysis," Neural Computing and Applications vol. 35, no. 21, pp. 15907-15921, 2023. https://doi.org/10.1007/s00521-023-08576-z
[11] E. Cambria, X. Zhang, R. Mao, M. Chen and K. Kwok, "SenticNet 8: Fusing emotion AI and commonsense AI for interpretable, trustworthy, and explainable affective computing," in International Conference on Human-Computer Interaction, Springer, 2024, pp. 197-216. https://doi.org/10.1007/978-3-031-76827-9_11
[12] A. Alsaeedi and M. Z. Khan, "A study on sentiment analysis techniques of Twitter data," International Journal of Advanced Computer Science and Applications, vol. 10, no. 2, 2019, https://doi.org/10.14569/ijacsa.2019.0100248
[13] A. K. Feroz, G. F. Khan and M. Sponder, Digital analytics for marketing. Routledge, 2024.
[14] A. L. Y. Tsang and D. K. Chiu, "Effectiveness of virtual reference services in academic libraries: A qualitative study based on the 5E learning model," The Journal of Academic Librarianship, vol. 48, no. 4, p. 102533, 2022. https://doi.org/10.1016/j.acalib.2022.102533
[15] A. H. C. Lam, K. K. Ho and D. K. Chiu, "Instagram for student learning and library promotions: a quantitative study using the 5E Instructional Model," Aslib Journal of Information Management, vol. 75, no. 1, pp. 112-130, 2023. https://doi.org/10.1108/AJIM-12-2021-0389
[16] B. Xue, R. Yao, Z. Ye, C. T. Chan, D. K. Chiu and Z. Zhong, "Social media analytics for academic music library: a case study of CUHK center for Chinese Music Studies," Library Hi Tech, vol. 43, no. 2/3, pp. 763-782, 2025. https://doi.org/10.1108/LHT-12-2023-0616
[17] K. Aalijah, "Utilizing Social Media Analytics to Detect Trends in Saudi Arabias Evolving Market," arXiv preprint arXiv:2502.16871, 2025. https://doi.org/10.48550/arXiv.2502.16871
[18] A. Rautiainen and J. Jokinen, "The value-relevance of social media activity of Finnish listed companies," International Journal of Accounting & Information Management, vol. 30, no. 2, pp. 301-323, 2022, https://doi.org/10.1108/IJAIM-04-2021-0076
[19] M. K. Hayat et al., "Towards deep learning prospects: insights for social media analytics," IEEE access, vol. 7, pp. 36958-36979, 2019. https://doi.org/10.1109/ACCESS.2019.2905101
[20] E. Cano-Marin, D. Ribeiro-Soriano, A. Mardani and C. B. Gonzalez-Tejero, "Exploring the challenges of the COVID-19 vaccine supply chain using social media analytics: a global perspective," Sustainable Technology and Entrepreneurship, vol. 2, no. 3, p. 100047, 2023. https://doi.org/10.1016/j.stae.2023.100047
[21] B. Prabaswara, W. Safira, K. Purwandari and F. I. Kurniadi, "Twitter sentiment analysis of Indonesian airlines using LSTM," in 2022 IEEE International Conference on Internet of Things and Intelligence Systems (IoTaIS), 2022: IEEE, pp. 386-389, https://doi.org/10.1109/IoTaIS56727.2022.9975946
[22] N. Darraz, I. Karabila, A. El-Ansari, N. Alami and M. El mallahi, "Optimizing Hybrid Recommendations: VADER-Enhanced Sentiment Analysis," in Proceedings of the 7th international conference on networking, intelligent systems and security, 2024, pp. 1-7. https://doi.org/10.1145/3659677.3659748
[23] N. Darraz, I. Karabila, A. El-Ansari, N. Alami and M. El Mallahi, "Integrated sentiment analysis with BERT for enhanced hybrid recommendation systems," Expert Systems with Applications, vol. 261, p. 125533, 2025. https://doi.org/10.1016/j.eswa.2024.125533
[24] G. Tian, L. Lu and C. McIntosh, "What factors affect consumers’ dining sentiments and their ratings: Evidence from restaurant online review data," Food Quality and Preference, vol. 88, p. 104060, 2021, https://doi.org/10.1016/j.foodqual.2020.104060
[25] Y. Seliverstov, S. Seliverstov, I. Malygin and O. Korolev, "Traffic safety evaluation in Northwestern Federal District using sentiment analysis of Internet users’ reviews," Transportation research procedia, vol. 50, pp. 626-635, 2020, https://doi.org/10.1016/j.trpro.2020.10.074
[26] I. Kandasamy, W. Vasantha, J. M. Obbineni and F. Smarandache, "Sentiment analysis of tweets using refined neutrosophic sets," Computers in Industry, vol. 115, p. 103180, 2020, https://doi.org/10.1016/j.compind.2019.103180
[27] I. Makki, W. Alhalabi and R. S. Adham, "Using emotion analysis to define human factors of virtual reality wearables," Procedia Computer Science, vol. 163, pp. 154-164, 2019, https://doi.org/10.1016/j.procs.2019.12.097
[28] A. Chaudhari, R. Raut, P. Randhavan and R. Rathod, "Comparison of Sentiment Analysis Algorithms Using Twitter Dataset for Real Time Analysis of Cricket Sport," in 2024 2nd International Conference on Intelligent Data Communication Technologies and Internet of Things (IDCIoT), 2024: IEEE, pp. 1415-1419, https://doi.org/10.1109/IDCIoT59759.2024.10467358
[29] F. Abid, J. Rasheed, M. Hamdi, H. Alshahrani, M. S. Al Reshan and A. Shaikh, "Sentiment analysis in social internet of things using contextual representations and dilated convolution neural network," Neural Computing and Applications, vol. 36, no. 20, pp. 12357-12370, 2024. https://doi.org/10.1007/s00521-024-09771-2
[30] G. Rizos, K. Hemker and B. Schuller, "Augment to prevent: short-text data augmentation in deep learning for hate-speech classification," in Proceedings of the 28th ACM international conference on information and knowledge management, 2019, pp. 991-1000, https://doi.org/10.1145/3357384.3358040
[31] J. A. Scheibmeir and Y. K. Malaiya, "Social media analytics of the Internet of Things," Discover Internet of Things, vol. 1, no. 1, p. 16, 2021. https://doi.org/10.1007/s43926-021-00016-5
[32] A. Sharma, J. Lyons, A. Dehzangi and K. K. Paliwal, "A feature extraction technique using bi-gram probabilities of position specific scoring matrix for protein fold recognition," Journal of theoretical biology, vol. 320, pp. 41-46, 2013, https://doi.org/10.1016/j.jtbi.2012.12.008
[33] D. Sharma, M. Sabharwal, V. Goyal, and M. Vij, "Sentiment analysis techniques for social media data: A review," in First International Conference on Sustainable Technologies for Computational Intelligence: Proceedings of ICTSCI 2019, Springer, 2019, pp. 75-90. https://doi.org/10.1007/978-981-15-0029-9_7
[34] A. Ritter, Mausam, O. Etzioni, and S. Clark, "Open domain event extraction from twitter," in Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining, 2012, pp. 1104-1112, https://doi.org/10.1145/2339530.23397
[35] S. Shayaa et al., "Sentiment analysis of big data: methods, applications, and open challenges," Ieee Access, vol. 6, pp. 37807-37827, 2018, https://doi.org/10.1109/ACCESS.2018.2851311
[36] J. P. Singh, S. Irani, N. P. Rana, Y. K. Dwivedi, S. Saumya and P. K. Roy, "Predicting the “helpfulness” of online consumer reviews," Journal of Business Research, vol. 70, pp. 346-355, 2017, https://doi.org/10.1016/j.jbusres.2016.08.008
[37] A. Kumar and A. Jaiswal, "Systematic literature review of sentiment analysis on Twitter using soft computing techniques," Concurrency and Computation: Practice and Experience, vol. 32, no. 1, p. e5107, 2020, https://doi.org/10.1002/cpe.5107
[38] K. Garcia and L. Berton, "Topic detection and sentiment analysis in Twitter content related to COVID-19 from Brazil and the USA," Applied soft computing, vol. 101, p. 107057, 2021, https://doi.org/10.1016/j.asoc.2020.107057
[39] S. Cherukuvada, K. Bellam, A. Soujanya and N. Krishnaraj, "Artificial Intelligence-Based Textual Cyberbullying Detection for Twitter Data Analysis in Cloud-Based Internet of Things," in Artificial Intelligence Techniques in IoT Sensor Networks: Chapman and Hall/CRC, 2020, pp. 151-166.
[40] S. J. Park, J. Y. Park, Y. S. Lim and H. W. Park, "Expanding the presidential debate by tweeting: The 2012 presidential election debate in South Korea," Telematics and informatics, vol. 33, no. 2, pp. 557-569, 2016, https://doi.org/10.1016/j.tele.2015.08.004
[41] S. Rouhani and E. Abedin, "Crypto-currencies narrated on tweets: a sentiment analysis approach," International Journal of Ethics and Systems, vol. 36, no. 1, pp. 58-72, 2020, https://doi.org/10.1108/IJOES-12-2018-0185
[42] A. Ajith, A. M. John and K. Joby, "Schematic Review on the Application of Blockchain and IoT Integration with Sentiment Analysis in Supply Chain Management," 2025 Emerging Technologies for Intelligent Systems (ETIS), pp. 1-6, 2025, https://doi.org/10.1109/ETIS64005.2025.10961615
[43] A. L. Duguma and X. Bai, "How the internet of things technology improves agricultural efficiency," Artificial