A “Deeper” Look at Detecting Cyberbullying in Social Networks

As cyberbullying becomes more and more frequent in social networks, automatically detecting it and pro-actively acting upon it becomes of the utmost importance. In this work, a detailed look at the current state-of-the-art in cyberbullying detection reveals that deep learning techniques have seldom been used to tackle this problem, despite growing reputation in other text-based classification tasks. Motivated by neural networks' documented success, three architectures are implemented from similar works: a simple CNN, a hybrid CNN-LSTM and a mixed CNN-LSTM-DNN. In addition, three text representations are trained from three different sources, via the word2vec model: Google-News, Twitter and Formspring. The experiment shows that these models with one of the above embeddings beat other benchmark classifiers (Support Vector Machines and Logistic Regression) both in an unbalanced and balanced version of the same dataset.

[1]  Abhijeet Sudhir Kasture,et al.  A predictive model to detect online cyberbullying , 2015 .

[2]  Hongxin Hu,et al.  Cyberbullying Detection with a Pronunciation Based Convolutional Neural Network , 2016, 2016 15th IEEE International Conference on Machine Learning and Applications (ICMLA).

[3]  Tony Veale,et al.  Fracking Sarcasm using Neural Network , 2016, WASSA@NAACL-HLT.

[4]  Jeffrey Dean,et al.  Efficient Estimation of Word Representations in Vector Space , 2013, ICLR.

[5]  April Kontostathis,et al.  Detecting the Presence of Cyberbullying Using Computer Software , 2011 .

[6]  Xiaojin Zhu,et al.  Fast learning for sentiment analysis on bullying , 2012, WISDOM '12.

[7]  Vikas S. Chavan,et al.  Machine learning approach for detection of cyber-aggressive comments by peers on social media network , 2015, 2015 International Conference on Advances in Computing, Communications and Informatics (ICACCI).

[8]  Quoc V. Le,et al.  Sequence to Sequence Learning with Neural Networks , 2014, NIPS.

[9]  Henry Lieberman,et al.  Common Sense Reasoning for Detection, Prevention, and Mitigation of Cyberbullying , 2012, TIIS.

[10]  Yoshua Bengio,et al.  Neural Machine Translation by Jointly Learning to Align and Translate , 2014, ICLR.

[11]  Byron C. Wallace,et al.  Modelling Context with User Embeddings for Sarcasm Detection in Social Media , 2016, CoNLL.

[12]  Guigang Zhang,et al.  Deep Learning , 2016, Int. J. Semantic Comput..

[13]  Yoon Kim,et al.  Convolutional Neural Networks for Sentence Classification , 2014, EMNLP.

[14]  Dolf Trieschnigg,et al.  Improving Cyberbullying Detection with User Context , 2013, ECIR.

[15]  Qianjia Huang,et al.  Cyber Bullying Detection Using Social and Textual Analysis , 2014, SAM '14.

[16]  Yann LeCun,et al.  Very Deep Convolutional Networks for Natural Language Processing , 2016, ArXiv.

[17]  Feng Luo,et al.  MCDefender: Toward Effective Cyberbullying Defense in Mobile Online Social Networks , 2017, IWSPA@CODASPY.

[18]  Yoshua Bengio,et al.  A Neural Probabilistic Language Model , 2003, J. Mach. Learn. Res..

[19]  Matthew Crosby,et al.  Association for the Advancement of Artificial Intelligence , 2014 .

[20]  Kelly Reynolds,et al.  Using Machine Learning to Detect Cyberbullying , 2011, 2011 10th International Conference on Machine Learning and Applications and Workshops.

[21]  Amit Awekar,et al.  Deep Learning for Detecting Cyberbullying Across Multiple Social Media Platforms , 2018, ECIR.

[22]  Henry Lieberman,et al.  Modeling the Detection of Textual Cyberbullying , 2011, The Social Mobile Web.

[23]  Alessandro Moschitti,et al.  Twitter Sentiment Analysis with Deep Convolutional Neural Networks , 2015, SIGIR.

[24]  Kasturi Dewi Varathan,et al.  Cybercrime detection in online communications: The experimental case of cyberbullying detection in the Twitter network , 2016, Comput. Hum. Behav..

[25]  Rui Zhao,et al.  Automatic detection of cyberbullying on social networks based on bullying features , 2016, ICDCN.

[26]  Zhiyuan Liu,et al.  A C-LSTM Neural Network for Text Classification , 2015, ArXiv.

[27]  Xue Li,et al.  An Effective Approach for Cyberbullying Detection , 2013 .