Research on Personalized Education Intervention Strategy Based on Barrage Emotional Analysis

Authors

  • Hui Zheng

DOI:

https://doi.org/10.54097/zqjebp71

Keywords:

Danmaku Sentiment Analysis, Personalized Education, Educational Intervention Strategies, Data Processing, Emotional Cognition, Empirical Research

Abstract

With the development of online teaching, the interactive feature of bullet comments has increasingly highlighted its potential in reflecting learners' emotional attitudes. This study employs bullet comment sentiment analysis as a tool to explore its application in personalized educational intervention. By collecting and processing bullet comment data and utilizing cutting-edge sentiment analysis techniques, the study aims to uncover learners' cognitive and emotional needs. Furthermore, this paper analyzes educational intervention strategies and focuses on the specific needs of personalized education. Through the construction of a scientific empirical research model, the effectiveness and practicality of sentiment analysis of bullet comments in personalized intervention strategies have been validated. Experimental results support the research hypothesis, indicating that sentiment analysis based on bullet comments plays a significant role in enhancing the personalization of educational intervention strategies. The conclusions of this study contribute to optimizing the online teaching environment and improving educational quality and efficiency.

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References

[1] Marchamalo, M Díaz-Redondo, F Morcillo, et al. Naturalising a heavily modified urban river: Initial habitat evolution in the Manzanares River (Madrid, Spain) [D]. River Research & Applications, 2022.W.-K. Chen, Linear Networks and Systems (Book style). Belmont, CA: Wadsworth, 1993, pp. 123–135.

[2] Ghosh K, Chakraborty T. Impact of human intervention structures on the rivers: An investigation of the spatiotemporal variation of grain size in the Tista River, eastern Himalayas[J]. Earth Surface Processes and Landforms: The journal of the British Geomorphological Research Group, 2022, 47(9):2245-2265.

[3] Yang Hongqiao. A study on the interaction behavior of viewers in educational videos with danmaku comments [J]. 2023.

[4] PK Shit, B Bera, A Islam, et al. Introduction to Drainage Basin Dynamics: Morphology, Landscape and Modelling [D]., 2022.

[5] Wang Chong, Zhang Yajun, Wang Juan. How does the general public perceive the application of generative artificial intelligence in education? - A public opinion and sentiment analysis of Bilibili's ChatGPT topic barrage text.

[6] Xu, Y. Research on the construction of short videos of collective memory of the COVID-19 pandemic[J].,2023.

[7] Li Danqi. Research on group identity based on the short video text of "The Post-00s" [J]. Communication Power Research, 2021.

[8] Sun Xiaofan. Aesthetic Culture Research on the Tagging of Barrage Comments[J]. 2024.

[9] Yang Tingting. Intertextuality Construction and Subjectivity Presentation in Danmu Culture[J].2023.

[10] Zhu Simiao, Wei Shiwei, Wei Siheng, et al. Video recommendation algorithm based on barrage sentiment analysis and topic model[J]. Computer Applications, 2021.

[11] Kang, K. (2022). A study on the influence of adolescent values orientation in the perspective of the interactive ritual chain theory.

[12] Wang G. Using and satisfying the circle-breaking perspective of Bilibili bullet screen culture[J].,2023.

[13] Lu Xia, Wu Shanfeng. Research on sentiment analysis of online classroom barrage comments based on neural networks[J]. Wireless Interconnect Technology, 2021.

[14] Chen Jiaqin, Yan Jiaxin. Gift exchange of young couples: Emotional analysis based on the "Rafi grass incident" B station barrage[J]. Youth Research and Practice, 2023.

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Published

18-09-2024

Issue

Section

Articles

How to Cite

Zheng, H. (2024). Research on Personalized Education Intervention Strategy Based on Barrage Emotional Analysis. Journal of Education and Educational Research, 10(2), 145-151. https://doi.org/10.54097/zqjebp71