@inproceedings{e6e3f62818f9462caae40c10f72dc4c3,
title = "Context-sensitive malicious spelling error correction",
abstract = "Misspelled words of the malicious kind work by changing specific keywords and are intended to thwart existing automated applications for cyber-environment control such as harassing content detection on the Internet and email spam detection. In this paper, we focus on malicious spelling correction, which requires an approach that relies on the context and the surface forms of targeted keywords. In the context of two applications-profanity detection and email spam detection-we show that malicious misspellings seriously degrade their performance. We then propose a context-sensitive approach for malicious spelling correction using word embeddings and demonstrate its superior performance compared to state-of-the-art spell checkers.",
keywords = "Cyberbullying, Machine learning, Malicious spelling correction",
author = "Hongyu Gong and Yuchen Li and Suma Bhat and Pramod Viswanath",
note = "Publisher Copyright: {\textcopyright} 2019 IW3C2 (International World Wide Web Conference Committee), published under Creative Commons CC-BY 4.0 License.; 2019 World Wide Web Conference, WWW 2019 ; Conference date: 13-05-2019 Through 17-05-2019",
year = "2019",
month = may,
day = "13",
doi = "10.1145/3308558.3313431",
language = "English (US)",
series = "The Web Conference 2019 - Proceedings of the World Wide Web Conference, WWW 2019",
publisher = "Association for Computing Machinery, Inc",
pages = "2771--2777",
booktitle = "The Web Conference 2019 - Proceedings of the World Wide Web Conference, WWW 2019",
}