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Modern Approaches to Detect and Classify Comment Toxicity Using Neural Networks
- Source :
- Modelirovanie i Analiz Informacionnyh Sistem, Vol 27, Iss 1, Pp 48-61 (2020)
- Publication Year :
- 2020
- Publisher :
- Yaroslavl State University, 2020.
-
Abstract
- The growth of popularity of online platforms which allow users to communicate with each other, share opinions about various events, and leave comments boosted the development of natural language processing algorithms. Tens of millions of messages per day are published by users of a particular social network need to be analyzed in real time for moderation in order to prevent the spread of various illegal or offensive information, threats and other types of toxic comments. Of course, such a large amount of information can be processed quite quickly only automatically. that is why there is a need to and a way to teach computers to “understand” a text written by humans. It is a non-trivial task even if the word “understand” here means only “to classify”. the rapid evolution of machine learning technologies has led to ubiquitous implementation of new algorithms. A lot of tasks, which for many years were considered almost impossible to solve, are now quite successfully solved using deep learning technologies. this article considers algorithms built using deep learning technologies and neural networks which can successfully solve the problem of detection and classification of toxic comments. In addition, the article presents the results of the developed algorithms, as well as the results of the ensemble of all considered algorithms on a large training set collected and tagged by Google and Jigsaw.
- Subjects :
- Word embedding
Computer science
02 engineering and technology
Information technology
Convolutional neural network
lstm
Task (project management)
World Wide Web
convolutional neural networks
0202 electrical engineering, electronic engineering, information engineering
recurrent neural networks
natural language processing
cnn
Artificial neural network
business.industry
gru
Deep learning
toxicity
deep learning
020206 networking & telecommunications
fasttext
nlp
word embedding
T58.5-58.64
Popularity
Recurrent neural network
020201 artificial intelligence & image processing
Artificial intelligence
business
glove
Word (computer architecture)
Subjects
Details
- Language :
- English
- ISSN :
- 23135417 and 18181015
- Volume :
- 27
- Issue :
- 1
- Database :
- OpenAIRE
- Journal :
- Modelirovanie i Analiz Informacionnyh Sistem
- Accession number :
- edsair.doi.dedup.....7c3fa6a7d462f93465479b7e91ba0c95