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Erschienen in: International Journal of Machine Learning and Cybernetics 5/2017

26.03.2016 | Original Article

Recognition of college students from Weibo with deep neural networks

verfasst von: Xiao Yu, Hua Yu, Xian-Yun Tian, Guang Yu, Xiao-mei Li, Xue Zhang, Ju-Yun Wang

Erschienen in: International Journal of Machine Learning and Cybernetics | Ausgabe 5/2017

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Abstract

Classification of college students is a key to conduct further research on students. In this paper, we collect a set of samples and build deep neural network classifiers to recognize them. We also analyze the experiences and behaviors of the college students on Weibo. Firstly, we manually label 1502 student users and 1498 non-college students. Then, the data about their posts are crawled from Weibo to be transformed into input vectors by feature engineering techniques. Finally, classifiers are built based on two deep learning algorithms, including stacked autoencoders and deep belief network. Experimental results show that deep neural networks performs better than other machine learning algorithms and the classification of the college students can achieve a very high accuracy.

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Metadaten
Titel
Recognition of college students from Weibo with deep neural networks
verfasst von
Xiao Yu
Hua Yu
Xian-Yun Tian
Guang Yu
Xiao-mei Li
Xue Zhang
Ju-Yun Wang
Publikationsdatum
26.03.2016
Verlag
Springer Berlin Heidelberg
Erschienen in
International Journal of Machine Learning and Cybernetics / Ausgabe 5/2017
Print ISSN: 1868-8071
Elektronische ISSN: 1868-808X
DOI
https://doi.org/10.1007/s13042-016-0515-1

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