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Sentiment Analysis Based on 100 Doctoral Acknowledgments

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DOI: 10.23977/jeis.2024.090322 | Downloads: 3 | Views: 173

Author(s)

Zhou Shihao 1

Affiliation(s)

1 College of Humanities and Social Development, Northwest A&F University, Yangling, Shaanxi, China

Corresponding Author

Zhou Shihao

ABSTRACT

This paper conducts sentiment analysis and LDA topic model on 100 doctoral thesis acknowledgement texts to explore the changes in emotional inclination and attitudes towards different subjects, events, and objects in the process of acknowledgement writing. The aim is to build a doctoral thesis acknowledgement corpus by collecting 28,152 segmented words and establish a time span of 2017-2024. The results are as follows: (1) There are five types of high-frequency words in doctoral acknowledgements: important interpersonal relationships (children, parents, etc.), key actions, focus objects, critical processes, and psychological feelings; (2) On a statistical level, the positive emotions in doctoral acknowledgements are significantly greater than the negative emotions. However, considerable negative emotions need to be paid attention to, such as anxiety and guilt; (3) The positive topics of doctoral acknowledgements include support and companionship, guidance and assistance, life, academic and school, and personal growth. The negative themes include thesis writing, research experience, mentor-disciple relationship, and institutional assistance.

KEYWORDS

LDA, Sentiment Analysis, Acknowledgments

CITE THIS PAPER

Zhou Shihao, Sentiment Analysis Based on 100 Doctoral Acknowledgments. Journal of Electronics and Information Science (2024) Vol. 9: 168-172. DOI: http://dx.doi.org/10.23977/10.23977/jeis.2024.090322.

REFERENCES

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[3] Yang Yihong, Wan Xiaoying, Wu Yishan. Analysis of the contents of acknowledgments of China's Top 100 Outstanding doctoral Theses in 2012 [J]. Journal of Information, 2014, 33(1): 62-66, 119.
[4] Traore Sekou Amadou. Socioeconomic and Perceptive Factors of HIV Transmission from Motherto Child in Bamako—Mali [D]. Central China Normal University, 2020.
[5] Liang Han, Hu Zhigang, Luo Wen, et al. The more sincere the gratitude, the more successful the future? Research on the relationship between the content of acknowledgments of doctoral theses and academic achievements based on fsQCA [J]. Library Forum, 2022, 42(11): 50-59.

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