Assessing the public perception of the fifth generation of mobile communication (5G) by sentiment analysis of Twitter users

Document Type : Original Article

Authors

1 Master of Information Technology Management e-business, Faculty of Social Sciences and Economics, Alzahra University, Tehran, Iran

2 Associate Professor, Department of Management, Faculty of Social Sciences and Economics, Alzahra University, Tehran, Iran

3 Assistant Professor, Department of Information Technology, Institute of Higher Education Mehralborz, Tehran, Iran

Abstract

With the development of mobile communications and the advent of the Fifth Generation, increasing Internet speed and capabilities as enablers of the Internet of Things is creating changes in people's daily lives and work. On the other hand, there are environmental issues, the possibility of pathogenicity, and doubts about the realization of the imagined features, which are much debated today. Most researches has paid attention to technical and developmental dimensions of it, while from the social science perspective, the acceptance of new technology and from the marketing perspective, consumer satisfaction can be important for service providers. Accordingly, the purpose of this study is to investigate the perception of Twitter social network users as a microblogging platform about the fifth generation of mobile communication using machine learning methods and Sentiment Analysis .Therefore, a collection of more than 40,000 tweets on this topic was compiled through the Twitter user interface and the Recurrent Neural Network model was created with79% accuracy. Finally, the topic modeling was done by LDA method for further deepening. The results shows that although there is dissatisfaction with the quality provided, the cost and coverage of the fifth generation of mobile communications, health concerns, rumors that Covid19 is related to the fifth generation, but still more people are optimistic about the future of this technology in various fields such as the Internet of Things and artificial intelligence..

Keywords

References

[1]    Y. Bin Zikria, S. W. Kim, M. K. Afzal, H. Wang, and M. H. Rehmani, “5G mobile services and scenarios: Challenges and solutions,” Sustain., vol. 10, no. 10, pp. 1–9, 2018, doi: 10.3390/su10103626.
[2]    C. L. Russell, “5 G wireless telecommunications expansion: Public health and environmental implications,” Environ. Res., vol. 165, pp. 484–495, Aug. 2018, doi: 10.1016/j.envres.2018.01.016.
[3]    A. N. Smith, E. Fischer, and C. Yongjian, “How Does Brand-related User-generated Content Differ across YouTube, Facebook, and Twitter?,” J. Interact. Mark., vol. 26, no. 2, pp. 102–113, 2012, doi: 10.1016/j.intmar.2012.01.002.
[4]    A. Zarei, D. Feiz, and G. Taheri, “Providing Social Market Intelligence Framework based on web 2.0 Using Text-Mining Technique on Social Media Websites (Case Study: Competitive Analysis between Samsung and Emersun Brands),” Management Research in Iran, vol. 24, no. 4, pp. 98–125, 2021. (in persian)
[5]    E. Dahlman, S. Parkvall, and J. Sköld, “What Is 5G?,” in 5G NR: the Next Generation Wireless Access Technology, 2018, pp. 1–6.
[6]    A. Bhardwaj, “5G for Military Communications,” in Procedia Computer Science, Jan. 2020, vol. 171, pp. 2665–2674, doi: 10.1016/j.procs.2020.04.289.
[7]    S. Forge and K. Vu, “Forming a 5G strategy for developing countries: A note for policy makers,” Telecomm. Policy, vol. 44, no. 7, p. 101975, Aug. 2020, doi: 10.1016/j.telpol.2020.101975.
[8]    A. Kumar and M. Gupta, “A review on activities of fifth generation mobile communication system,” Alexandria Engineering Journal, vol. 57, no. 2. Elsevier B.V., pp. 1125–1135, Jun. 01, 2018, doi: 10.1016/j.aej.2017.01.043.
[9]    D. A. Meshram and D. D. Patil, “5G Enabled Tactile Internet for Tele-Robotic Surgery,” in Procedia Computer Science, Jan. 2020, vol. 171, pp. 2618–2625, doi: 10.1016/j.procs.2020.04.284.
[10] R. Ye et al., “Journal Pre-proof Feasibility of a 5G-based robot-assisted remote ultrasound system for cardiopulmonary assessment of COVID-19 patients,” 2020, doi: 10.1016/j.chest.2020.06.068.
[11] Z. M. Temesvári, D. Maros, and P. Kádár, “Review of Mobile Communication and the 5G in Manufacturing,” in Procedia Manufacturing, Jan. 2019, vol. 32, pp. 600–612, doi: 10.1016/j.promfg.2019.02.259.
[12] J. S. Walia, H. Hämmäinen, K. Kilkki, and S. Yrjölä, “5G network slicing strategies for a smart factory,” Comput. Ind., vol. 111, pp. 108–120, 2019, doi: 10.1016/j.compind.2019.07.006.
[13] R. N. Kostoff, P. Heroux, M. Aschner, and A. Tsatsakis, “Adverse health effects of 5G mobile networking technology under real-life conditions,” Toxicol. Lett., vol. 323, pp. 35–40, 2020, doi: 10.1016/j.toxlet.2020.01.020.
[14] D. C. Nguyen, P. N. Pathirana, M. Ding, and A. Seneviratne, “Blockchain for 5G and beyond networks: A state of the art survey,” Journal of Network and Computer Applications, vol. 166. Academic Press, p. 102693, Sep. 15, 2020, doi: 10.1016/j.jnca.2020.102693.
[15] S. Sicari, A. Rizzardi, and A. Coen-Porisini, “5G In the internet of things era: An overview on security and privacy challenges,” Comput. Networks, vol. 179, p. 107345, Oct. 2020, doi: 10.1016/j.comnet.2020.107345.
[16] I. Mistry, S. Tanwar, S. Tyagi, and N. Kumar, “Blockchain for 5G-enabled IoT for industrial automation: A systematic review, solutions, and challenges,” Mech. Syst. Signal Process., vol. 135, p. 106382, Jan. 2020, doi: 10.1016/j.ymssp. 2019.106382.
[17] M. Rostami, S. Heydariyeh, and A. Beidokhti, “Provide a Digital Content Marketing Model due to Consumer Value Creation,” Management Research in Iran, vol. 26, no. 1, pp. 112–137, 2022(in persian)
[18] D. M. E. D. M. Hussein, “A survey on sentiment analysis challenges,” J. King Saud Univ. - Eng. Sci., vol. 30, no. 4, pp. 330–338, Oct. 2018, doi: 10.1016/j.jksues.2016.04.002.
[19] F. Abbasi, A. Khadivar, and M. Yazdinejad, “A Grouping Hotel Recommender System Based on Deep Learning and Sentiment Analysis,” J. Inf. Technol. Manag., vol. 11, no. 2, pp. 59–78, Jun. 2019, doi: 10.22059/JITM.2019.289271.2402. 
[20] S. Dipti, S. Munish, V. Goya, and M. Vij, “Sentiment Analysis Techniques for Social Media Data: A Review,” in Advances in Intelligent Systems and Computing, vol. 1045, spriner nature sinapore, 2020, pp. 75–90.
[21] A. Gulli and S. Pal, Deep Learning with Keras. 2017.
[22] K. El Bouchefry and R. S. de Souza, “Learning in Big Data: Introduction to Machine Learning,” in Knowledge Discovery in Big Data from Astronomy and Earth Observation, Elsevier, 2020, pp. 225–249.
[23] S. Prabhakaran, “Gensim Topic Modeling - A Guide to Building Best LDA models,” Machine Learning plus, 2018. https://www.machinelearningplus .com/nlp/topic-modeling-gensim-python/ (accessed Mar. 09, 2021).
[24] D. Subramanian, “Text Preprocessing for Data Scientists,” Towards Data Science, 2019. https://towardsdatascience.com/text-preprocessing-for-data-scientist-3d2419c8199d (accessed Feb. 24, 2021).
[25] T. Tajani Kouchaki, A. Mohtashami, M. Amiri, and R. E. Rasi, “Designing an improved Adaptive Neuro-Fuzzy Inference System based on Whale Optimization Algorithm to predict blood donation,” Modern Research in Decision Making. (in persian)
[26] F. Kamari, A. Saranj, R. Tehrani, and M. Shahbazi, “Model design for stock statistical arbitrage using deep neural networks, random forests and gradient-boosted trees,” Modern Research in Decision Making., vol. 4, no. 3, pp. 23–45, 2019.(in persian)
[27] Carvia Tech, “Difference between Loss, Accuracy, Validation loss, Validation accuracy in Keras,” 2019. https://www.javacodemonk.com/difference-between-loss-accuracy-validation-loss-validation-accuracy-in-keras-ff358faa (accessed Mar. 01, 2021).
[28] F. Abbasi and A. Khadivar, “Comparing the effect of sentiment analysis and user ratings on the performance of recommender systems.,” ORMR, vol. 11, no. 4, pp. 75–92, 2022. (in persian)
[29] T. Seckin and Z. H. Kilimci, “The Evaluation of 5G technology from Sentiment Analysis Perspective in Twitter,” in 2020 Innovations in Intelligent Systems and Applications Conference (ASYU), Oct. 2020, pp. 1–6, doi: 10.1109/ASYU50717.2020.9259900.
[30] A. A. Herrera-Contreras, E. Sánchez-Delacruz, and I. V. Meza-Ruiz, “Twitter Opinion Analysis About Topic 5G Technology,” in Communications in Computer and Information Science, 2020, vol. 1193 CCIS, pp. 191–203, doi: 10

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