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Botgraph: Large scale spamming botnet detection
F. Y. Q. K. Y. Y. Y. C. Yao Zhao, Yinglian Xie and E. Gillum · 2009
Earlier work this paper cites.
Common sense reasoning for detection, prevention, and mitigation of cyberbullying
C. H. H. L. Karthik Dinakar, Birago Jones and R. Picard · 2012
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Analyzing spammers’ social networks for fun and profit: a case study of cyber criminal ecosystem on twitter
C. Yang, R. Harkreader, J. Zhang, S. Shin, and G. Gu · 2012
Earlier work this paper cites.
Detecting offensive language in social media to protect adolescent online safety
S. Z. H. X. Ying Chen, Yilu Zhou · 2012
Earlier work this paper cites.
Improving cyberbullying detection with user context
R. O. Maral Dadvar, Dolf Trieschnigg and F. de Jong · 2013
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Integro: Leveraging victim prediction for robust fake account detection in osns
Y. Boshmaf, D. Logothetis, G. Siganos, J. Lería, J. Lorenzo, M. Ripeanu, and K. Beznosov · 2015
Earlier work this paper cites.
Detection of cyberbullying incidents on the instagram social network
R. I. R. R. H. Q. L. S. M. Homa Hosseinmardi, Sabrina Arredondo Mattson · 2015
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Hate speech detection with comment embeddings
R. M. M. G. V. R. N. B. Nemanja Djuric, Jing Zhou · 2015
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Detecting clusters of fake accounts in online social networks
C. Xiao, D. M. Freeman, and T. Hwa · 2015
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A critical review of recurrent neural networks for sequence learning
C. E. Zachary Lipton, John Berkowitz · 2015
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Abusive language detection in online user content
A. T. Y. M. Y. M. Chikashi Nobata, Joel Tetreault · 2016
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Content-driven detection of cyberbullying on the instagram social network
A. S. S. R. C. G. D. M. C. C. Haoti Zhong, Hao Li · 2016
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Detecting rumors from microblogs with recurrent neural networks
P. M. H. B. K. S. K. B. J. J. K.-F. W. M. C. Jing Ma, Wei Gao · 2016
Cited alongside, same era.
In a world that counts: Clustering and detecting fake social engagement at scale
Y. Li, O. Martinez, X. Chen, Y. Li, and J. E. Hopcroft · 2016
Cited alongside, same era.
Us and them: identifying cyber hate on twitter across multiple protected characteristics
M. L. W. Pete Burnap · 2016
Cited alongside, same era.
Rumor identification and belief investigation on twitter
M. T. D. Sardar Hamidian · 2016
Cited alongside, same era.
Hateful symbols or hateful people? predictive features for hate speech detection on twitter
D. H. Zeerak Waseem · 2016
Cited alongside, same era.
A survey on hate speech detection using natural language processing
M. W. Anna Schmidt · 2017
Detection and resolution of rumours in social media: A survey
K. B. M. L. R. P. Arkaitz Zubiaga, Ahmet Aker · 2018
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Fakebuster: A robust fake account detection by activity analysis
Y.-C. Chen and S. F. Wu · 2018
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Efficient large-scale multi-modal classification
A. J. T. M. Douwe Kiela, Edouard Grave · 2018
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Leveraging deep neural networks to fight child pornography in the age of social media
M. P. A. R. Paulo Vitorino, Sandra Avila · 2018
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https://transparency.facebook.com/community-standards-enforcement#bullying-and-harassment
Facebook transparency report - bullying and harassment · 2019
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https://transparency.facebook.com/community-standards-enforcement#hate-speech
Facebook transparency report - hate speech · 2019
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Cited alongside, same era.
A convolutional approach for misinformation identification
S. W. L. W. T. T. Feng Yu, Qiang Liu · 2017
Cited alongside, same era.
Using convolutional neural networks to classify hate-speech
B. Gambäck and U. K. Sikdar · 2017
Cited alongside, same era.
Deep sets
S. R. B. P. R. S. A. J. S. Manzil Zaheer, Satwik Kottur · 2017
Cited alongside, same era.
Poised: Spotting twitter spam off the beaten paths
S. Nilizadeh, F. Labrèche, A. Sedighian, A. Zand, J. Fernandez, C. Kruegel, G. Stringhini, and G. Vigna · 2017
Cited alongside, same era.
Deep learning for hate speech detection in tweets
M. G. V. V. Pinkesh Badjatiya, Shashank Gupta · 2017
Cited alongside, same era.
Attention is all you need
A. Vaswani, N. Shazeer, N. Parmar, J. Uszkoreit, L. Jones, A. N. Gomez, Ł. Kaiser, and I. Polosukhin · 2017
Cited alongside, same era.
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A survey of the recent architectures of deep convolutional neural networks
U. Z. A. S. Q. Asifullah Khan, Anabia Sohail · 2019
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Predicting dynamic embedding trajectory in temporal interaction networks
S. Kumar, X. Zhang, and J. Leskovec · 2019
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Pytorch-biggraph: A large-scale graph embedding system
A. Lerer, L. Wu, J. Shen, T. Lacroix, L. Wehrstedt, A. Bose, and A. Peysakhovich · 2019
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https://www.facebook.com/business/success/categories/small-business
Facebook for small businesses · 2020
Closest in time.
https://pytorch.org/docs/stable/jit.html
Torchscript documentation · 2020
Closest in time.