F. Alam, M. Imran, and F. Ofli, Image4act: Online social media image processing for disaster response, Proceedings of the 2017 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, pp.601-604, 2017.

S. T. Aroyehun and A. Gelbukh, Aggression detection in social media: Using deep neural networks, data augmentation, and pseudo labeling, Proceedings of the First Workshop on Trolling, Aggression and Cyberbullying (TRAC-2018), pp.90-97, 2018.

I. Arroyo-fernández, D. Forest, J. M. Torres-moreno, M. Carrasco-ruiz, T. Legeleux et al., Cyberbullying detection task: the ebsi-lia-unam system (elu) at coling'18 trac-1, Proceedings of the First Workshop on Trolling, Aggression and Cyberbullying, pp.140-149, 2018.

D. Chatzakou, N. Kourtellis, J. Blackburn, E. De-cristofaro, G. Stringhini et al., Mean birds: Detecting aggression and bullying on twitter, Proceedings of the 2017 ACM on web science conference, pp.13-22, 2017.

V. S. Chavan and S. Shylaja, Machine learning approach for detection of cyberaggressive comments by peers on social media network, Advances in computing, communications and informatics (ICACCI), 2015 International Conference on, pp.2354-2358, 2015.

J. Chen, S. Yan, and K. C. Wong, Verbal aggression detection on twitter comments: convolutional neural network for short-text sentiment analysis, Neural Computing and Applications, pp.1-10, 2018.

M. Dadvar, D. Trieschnigg, J. De, and F. , Experts and machines against bullies: A hybrid approach to detect cyberbullies, Canadian Conference on Artificial Intelligence, pp.275-281, 2014.

D. W. Grigg, Cyber-aggression: Definition and concept of cyberbullying, Journal of Psychologists and Counsellors in Schools, vol.20, issue.2, pp.143-156, 2010.

H. Hosseinmardi, R. I. Rafiq, R. Han, Q. Lv, and S. Mishra, Prediction of cyberbullying incidents in a media-based social network, 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), pp.186-192, 2016.

J. Kornblum, Cyberbullying grows bigger and meaner with photos

A. Krizhevsky, I. Sutskever, and G. E. Hinton, Imagenet classification with deep convolutional neural networks, Advances in neural information processing systems, pp.1097-1105, 2012.

A. D. League, Glossary of cyberbullying terms. adl. org, 2011.

H. Machackova, L. Dedkova, A. Sevcikova, and A. Cerna, Bystanders supportive and passive responses to cyberaggression, Journal of school violence, vol.17, issue.1, pp.99-110, 2018.

K. L. Modecki, B. L. Barber, and L. Vernon, Mapping developmental precursors of cyber-aggression: Trajectories of risk predict perpetration and victimization, Journal of youth and adolescence, vol.42, issue.5, pp.651-661, 2013.

S. Modha, P. Majumder, and T. Mandl, Filtering aggression from the multilingual social media feed, Proceedings of the First Workshop on Trolling, Aggression and Cyberbullying (TRAC-2018), pp.199-207, 2018.

D. T. Nguyen, F. Ofli, M. Imran, and P. Mitra, Damage assessment from social media imagery data during disasters, Proceedings of the 2017 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, pp.569-576, 2017.

D. T. Nguyen, F. Alam, F. Ofli, and M. Imran, Automatic image filtering on social networks using deep learning and perceptual hashing during crises, 2017.

J. A. Pater, A. D. Miller, and E. D. Mynatt, This digital life: A neighborhood-based study of adolescents' lives online, Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems, pp.2305-2314, 2015.

R. Paul, Classifying cooking object's state using a tuned vgg convolutional neural network, 2018.

K. Raiyani, T. Gonçalves, P. Quaresma, and V. B. Nogueira, Fully connected neural network with advance preprocessor to identify aggression over facebook and twitter, Proceedings of the First Workshop on Trolling, Aggression and Cyberbullying, pp.28-41, 2018.

J. Risch and R. Krestel, Aggression identification using deep learning and data augmentation, Proceedings of the First Workshop on Trolling, Aggression and Cyberbullying (TRAC-2018), pp.150-158, 2018.

M. Rybnicek, R. Poisel, and S. Tjoa, Facebook watchdog: a research agenda for detecting online grooming and bullying activities, Systems, Man, and Cybernetics (SMC), 2013 IEEE International Conference on, pp.2854-2859, 2013.

S. Salawu, Y. He, and J. Lumsden, Approaches to automated detection of cyberbullying: A survey, IEEE Transactions on Affective Computing, issue.1, pp.1-1, 2017.

N. S. Samghabadi, D. Mave, S. Kar, and T. Solorio, Ritual-uh at trac 2018 shared task: Aggression identification, 2018.

S. J. Seiler and J. N. Navarro, Bullying on the pixel playground: Investigating risk factors of cyberbullying at the intersection of childrens online-offline social lives, Cyberpsychology: Journal of Psychosocial Research on Cyberspace, vol.8, issue.4, 2014.

R. L. Servance, Cyberbullying, cyber-harassment, and the conflict between schools and the first amendment, Wis. L. Rev. p, p.1213, 2003.

K. Simonyan and A. Zisserman, Very deep convolutional networks for large-scale image recognition, 2014.

V. K. Singh, S. Ghosh, and C. Jose, Toward multimodal cyberbullying detection, Proceedings of the 2017 CHI Conference Extended Abstracts on Human Factors in Computing Systems, pp.2090-2099, 2017.

S. Srivastava, P. Khurana, and V. Tewari, Identifying aggression and toxicity in comments using capsule network, Proceedings of the First Workshop on Trolling, Aggression and Cyberbullying (TRAC-2018), pp.98-105, 2018.

K. Van-royen, K. Poels, W. Daelemans, and H. Vandebosch, Automatic monitoring of cyberbullying on social networking sites: From technological feasibility to desirability, Telematics and Informatics, vol.32, issue.1, pp.89-97, 2015.