@inproceedings{kim-etal-2020-analysis,
title = "Analysis of Online Conversations to Detect Cyberpredators Using Recurrent Neural Networks",
author = "Kim, Jinhwa and
Kim, Yoon Jo and
Behzadi, Mitra and
Harris, Ian G.",
editor = "Bhatia, Archna and
Shaikh, Samira",
booktitle = "Proceedings for the First International Workshop on Social Threats in Online Conversations: Understanding and Management",
month = may,
year = "2020",
address = "Marseille, France",
publisher = "European Language Resources Association",
url = "https://aclanthology.org/2020.stoc-1.3",
pages = "15--20",
abstract = "We present an automated approach to analyze the text of an online conversation and determine whether one of the participants is a cyberpredator who is preying on another participant. The task is divided into two stages, 1) the classification of each message, and 2) the classification of the entire conversation. Each stage uses a Recurrent Neural Network (RNN) to perform the classification task.",
language = "English",
ISBN = "979-10-95546-39-9",
}
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<abstract>We present an automated approach to analyze the text of an online conversation and determine whether one of the participants is a cyberpredator who is preying on another participant. The task is divided into two stages, 1) the classification of each message, and 2) the classification of the entire conversation. Each stage uses a Recurrent Neural Network (RNN) to perform the classification task.</abstract>
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%0 Conference Proceedings
%T Analysis of Online Conversations to Detect Cyberpredators Using Recurrent Neural Networks
%A Kim, Jinhwa
%A Kim, Yoon Jo
%A Behzadi, Mitra
%A Harris, Ian G.
%Y Bhatia, Archna
%Y Shaikh, Samira
%S Proceedings for the First International Workshop on Social Threats in Online Conversations: Understanding and Management
%D 2020
%8 May
%I European Language Resources Association
%C Marseille, France
%@ 979-10-95546-39-9
%G English
%F kim-etal-2020-analysis
%X We present an automated approach to analyze the text of an online conversation and determine whether one of the participants is a cyberpredator who is preying on another participant. The task is divided into two stages, 1) the classification of each message, and 2) the classification of the entire conversation. Each stage uses a Recurrent Neural Network (RNN) to perform the classification task.
%U https://aclanthology.org/2020.stoc-1.3
%P 15-20
Markdown (Informal)
[Analysis of Online Conversations to Detect Cyberpredators Using Recurrent Neural Networks](https://aclanthology.org/2020.stoc-1.3) (Kim et al., STOC 2020)
ACL