Abstract
The explosion of social networks has created many new careers and new entertainment. Money now can be earned by sitting in one place and streaming games; reviewing food, movies, music; or just simply showing a pretty face. Social networks make all of those things, and more, possible. As long as a person is famous on social networks, they can earn money by doing almost everything. So how to be famous, or in social network’s language, what gets someone “followers” on social media? Is being positive, telling funny stories, showing sunshine and flower pictures enough? Or they can be a pessimistic person, ranting about everything and people still worship them like a god? This research collects and analyses hot Facebook users posts’ sentiment to see if what someone posts on Facebook could make them famous and also determines the accuracy of using deep learning in analysing Vietnamese social media contents sentiment. There have been several studies for social media content sentiment analysing, but none with Vietnamese social media contents of famous Vietnamese people. In this study, a data set of Vietnamese hot Facebook users’ posts is labelled and organized to be shared with the language research community generally, and the Vietnamese language research specifically.
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Ngoc Tram, N., Duy Hung, P. (2021). Analysing Hot Facebook Users Posts’ Sentiment Using Deep Learning. In: Hassanien, A.E., Bhattacharyya, S., Chakrabati, S., Bhattacharya, A., Dutta, S. (eds) Emerging Technologies in Data Mining and Information Security. Advances in Intelligent Systems and Computing, vol 1300. Springer, Singapore. https://doi.org/10.1007/978-981-33-4367-2_53
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