Recognition of college students from Weibo with deep neural networks

Recognition of college students from Weibo with deep neural networks 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. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Machine Learning and Cybernetics Springer Journals

Recognition of college students from Weibo with deep neural networks

Loading next page...
 
/lp/springer_journal/recognition-of-college-students-from-weibo-with-deep-neural-networks-I03SV1E7Eg
Publisher
Springer Berlin Heidelberg
Copyright
Copyright © 2016 by Springer-Verlag Berlin Heidelberg
Subject
Engineering; Computational Intelligence; Artificial Intelligence (incl. Robotics); Control, Robotics, Mechatronics; Complex Systems; Systems Biology; Pattern Recognition
ISSN
1868-8071
eISSN
1868-808X
D.O.I.
10.1007/s13042-016-0515-1
Publisher site
See Article on Publisher Site

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.

Journal

International Journal of Machine Learning and CyberneticsSpringer Journals

Published: Mar 26, 2016

References

You’re reading a free preview. Subscribe to read the entire article.


DeepDyve is your
personal research library

It’s your single place to instantly
discover and read the research
that matters to you.

Enjoy affordable access to
over 18 million articles from more than
15,000 peer-reviewed journals.

All for just $49/month

Explore the DeepDyve Library

Search

Query the DeepDyve database, plus search all of PubMed and Google Scholar seamlessly

Organize

Save any article or search result from DeepDyve, PubMed, and Google Scholar... all in one place.

Access

Get unlimited, online access to over 18 million full-text articles from more than 15,000 scientific journals.

Your journals are on DeepDyve

Read from thousands of the leading scholarly journals from SpringerNature, Elsevier, Wiley-Blackwell, Oxford University Press and more.

All the latest content is available, no embargo periods.

See the journals in your area

DeepDyve

Freelancer

DeepDyve

Pro

Price

FREE

$49/month
$360/year

Save searches from
Google Scholar,
PubMed

Create lists to
organize your research

Export lists, citations

Read DeepDyve articles

Abstract access only

Unlimited access to over
18 million full-text articles

Print

20 pages / month

PDF Discount

20% off