Deep Learning for Multi-Class Antisocial Behavior Identification From Twitter
Download
09222124.pdf
- Published Version
(2MB)
| Preview
Available under license: Creative Commons Attribution
Export
Singh, Ravinder, Subramani, Sudha ORCID: 0000-0002-8102-0278, Du, Jiahua, Zhang, Yanchun
ORCID: 0000-0002-5094-5980, Wang, Hua
ORCID: 0000-0002-8465-0996, Ahmed, Khandakar
ORCID: 0000-0003-1043-2029 and Chen, Zhenxiang
ORCID: 0000-0002-4948-3803
(2020)
Deep Learning for Multi-Class Antisocial Behavior Identification From Twitter.
IEEE Access, 8.
pp. 194027-194044.
ISSN 2169-3536
Dimensions Badge
Altmetric Badge
Item type | Article |
URI | https://vuir.vu.edu.au/id/eprint/41846 |
DOI | 10.1109/ACCESS.2020.3030621 |
Official URL | https://ieeexplore.ieee.org/document/9222124 |
Subjects | Historical > FOR Classification > 0801 Artificial Intelligence and Image Processing Current > Division/Research > Institute for Sustainable Industries and Liveable Cities |
Keywords | deep learning, Recurrent Neural Network , Convolutional Neural Networks, architectures, word embeddings of text data, gold standard data set, visualization, personality disorder, online antisocial behaviour |
Citations in Scopus | 5 - View on Scopus |
Download/View statistics | View download statistics for this item |
CORE (COnnecting REpositories)