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The Role of Computational Stylometry in Identifying (Misogynistic) Aggression in English Social Media Texts

机译:计算风格识别在识别英语社交媒体文本中的(同性恋)侵略中的作用

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In this paper, we describe UniOr_ExpSys team participation in TRAC-2 (Trolling, Aggression and Cyberbullying) shared task, a workshop organized as part of LREC 2020. TRAC-2 shared task is organized in two sub-tasks: Aggression Identification (a 3-way classification between "Overtly Aggressive", "Covertly Aggressive" and "Non-aggressive" text data) and Misogynistic Aggression Identification (a binary classifier for classifying the texts as "gendered" or "non-gendered"). Our approach is based on linguistic rules, stylistic features extraction through stylometric analysis and Sequential Minimal Optimization algorithm in building the two classifiers.
机译:在本文中,我们描述UniOr_ExpSys团队参与TRAC-2(拖钓,侵略和网络欺凌)共享任务的过程,该任务是LREC 2020的一部分。TRAC-2共享任务分为两个子任务:攻击识别(a 3 “攻击性”,“攻击性”和“非攻击性”文本数据之间的双向分类和误配性攻击识别(将文本分类为“性别”或“非性别”的二进制分类器)。我们的方法是基于语言规则,通过笔法分析提取的文体特征以及建立这两个分类器的顺序最小优化算法。

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