Abstract
The metaverse is referred to as a virtual reality space, integrating the real world with the digital world. People have gained interest in this as many well-known companies like Facebook are entering this world of the metaverse. Most people are curious about the possibilities and future of the metaverse considering the various prospective applications it is going to offer like virtual meetings, learning environments and many more. However, there are also worries about potential negative effects as in the metaverse signals from the real world can be transmitted in the virtual world. In this regard, people express their feelings on various social media platforms. The various data obtained from this social media platform is a popular study subject as it gives an important insight into the thoughts of society towards a new event. Thus, in this work twitter, which is one of the extensive social media platforms internationally used to express thoughts, is chosen as the platform of study. Tweets are analyzed to assess people’s attitudes and tendencies towards an event. In the present generation, people express themselves not only with words but also emojis. Therefore, in this paper tweets compromising of both text and emojis are considered for analyzing human sentiments towards the metaverse and the potential risk associated with it. The dataset is compromises of tweets having the word the metaverse and hashtags the metaverse. Observed analysis shows an improvement of over 2.92% for the proposed method.
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References
Arali, Ö., Aydin, Ö.: Tweet classification and sentiment analysis on the metaverse related messages. J. metaverse 1(1), 25–30 (2021)
Hayawi, K., Shahriar, S., Serhani, M.A., Alothali, E.: Inevitable the metaverse: a novel twitter dataset for public sentiments on the metaverse (2022)
Akkuzukaya, G.: Sentiment analysis on the the metaverse: twitter data. Sakarya Univ. J. Comput. Inf. Sci. 5(2), 147–156 (2022)
LeCompte, T., Chen, J.: Sentiment analysis of tweets including emoji data. In 2017 International Conference on Computational Science and Computational Intelligence (CSCI), pp. 793–798 (2017)
Young, M.K., Rieser, J.J., Bodenheimer, B.: Dyadic interactions with avatars in immersive virtual environments: high fiving. In: Proceedings of the ACM SIGGRAPH Symposium on Applied Perception, pp. 119–126 (2015)
Wei, Y., Qin, X., Tan, X., Yu, X., Sun, B., Zhu, X.: The design of a visual tool for the quick customization of virtual characters in OSSL. In: 2015 International Conference on Cyberworlds (CW), pp. 314–320. IEEE (2015)
Duan, H., Li, J., Fan, S., Lin, Z., Wu, X., Cai, W.: The metaverse for social good: a university campus prototype. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 153–161 (2021)
Chaturvedi, I., Cambria, E., Welsch, R.E., Herrera, F.: Distinguishing between facts and opinions for sentiment analysis: survey and challenges. Inf. Fusion 44, 65–77 (2018)
Ullah, M.A., Marium, S.M., Begum, S.A., Dipa, N.S.: An algorithm and method for sentiment analysis using the text and emoticon. ICT Express 6(4), 357–360 (2020)
Roy, S., Patel, B., Bhattacharyya, D., Dhayal, K., Kim, T.-H., Mittal, M.: Demographical gender prediction of twitter users using big data analytics: an application of decision marketing. Int. J. Reason. Based Intell. Syst. 13(2), 41–49 (2021)
Geetika Vashisht, M.J.: Emoticons emojis based sentiment analysis: the last two decades! Int. J. Sci. Technol. Res. 9(3) (2020)
Atif, M., Franzoni, V.: Tell me more: automating emojis classification for better accessibility and emotional context recognition. Future Internet 14(5), 142 (2022)
Liu, C., et al.: Improving sentiment analysis accuracy with emoji embedding. J. Saf. Sci. Resil. 2(4), 246–252 (2021)
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Bhattacharyya, M., Roy, A., Midya, S., Mitra, A., Ghosh, A., Roy, S. (2023). An Emoticon-Based Sentiment Aggregation on Metaverse Related Tweets. In: Hassanien, A.E., et al. The 3rd International Conference on Artificial Intelligence and Computer Vision (AICV2023), March 5–7, 2023. AICV 2023. Lecture Notes on Data Engineering and Communications Technologies, vol 164. Springer, Cham. https://doi.org/10.1007/978-3-031-27762-7_34
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DOI: https://doi.org/10.1007/978-3-031-27762-7_34
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