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State of Low-power Wireless Protocols for IoT
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Talk, Joel Tetreault, May 24 2017
When Words Cause Harm: Automatic Detection of Abusive Language Online
Detection of abusive language in user generated online content has become an issue of increasing importance in recent years. For instance, cyberbullying and other forms of online harassment have forced many users to remove their accounts, and large internet companies have struggled to identify and filter abusiveposts and users. Most current commercial methods make use of blacklists and regular expressions
these measures fall short when contending with more subtle, less ham-fisted examples of hate speech. In this talk, we present a machine learning based method to detect hate speech in online user comments from two domains which outperform a state-of-the-art deep learning approach. We also develop a corpus of user comments annotated for abusive language, the first of its kind. Finally, we use our detection tool to analyze abusive language over time and in different settings to further enhance our knowledge of this behavior.
is Director of Research at Grammarly. His research focus is Natural Language Processing with specific interests in anaphora, dialogue and discourse processing, machine learning, and applying these techniques to the analysis of English language learning, automated essay scoring among others. Currently he works on the research and development of NLP tools and components for the next generation of intelligent writing assistance systems. Prior to joining Grammarly, he was a Senior Research Scientist at Yahoo Labs, Senior Principal Manager of the Core Natural Language group at Nuance Communications, Inc., and worked at Educational Testing Service for six years as a managing research scientist where he researched automated methods for essay scoring, detecting grammatical errors by non-native speakers, plagiarism detection, and content scoring. Tetreault received his B.A. in Computer Science from Harvard University and his M.S. and Ph.D. in Computer Science from the University of Rochester. He was also a postdoctoral research scientist at the University of Pittsburgh's Learning Research and Development Center, where he worked on developing spoken dialogue tutoring systems. In addition, he has co-organized the Building Educational Application workshop series for 8 years, several shared tasks, and is currently NAACL Treasurer.
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