Authorship verification for short messages using stylometry
Authorship verification for short messages using stylometry
复制标题
使用文体测量法验证短信的作者身份
DOI：
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发表时间：
2013
期刊：
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通讯作者：
I. Woungang
中科院分区：
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作者：
Marcelo Luiz Brocardo;I. Traoré;Sherif Saad;I. Woungang
作者身份的确认可以通过分析作者的语言风格和写作特点，使用文体计量学技术来进行。文体学是一种行为特征，一个人在写作过程中表现出来，可以提取并用于检查在线文档作者的身份。虽然文体测量技术可以实现高准确率的长文档，它仍然是具有挑战性的，以确定一个作者的短文档，特别是当处理大量的作者群体。这些障碍必须得到解决，才能让文体学在检查电子邮件、短信或twitter提要等在线信息的作者身份时发挥作用。在本文中，我们提出了一些实现这一目标的步骤，提出了一个监督学习技术结合n-gram分析的作者身份验证短文本。实验评估的基础上安然电子邮件数据集，涉及87位作者产生非常有前途的结果，包括一个相等的错误率（EER）为14.35%的消息块的500个字符。
Authorship verification can be checked using stylometric techniques through the analysis of linguistic styles and writing characteristics of the authors. Stylometry is a behavioral feature that a person exhibits during writing and can be extracted and used potentially to check the identity of the author of online documents. Although stylometric techniques can achieve high accuracy rates for long documents, it is still challenging to identify an author for short documents, in particular when dealing with large authors populations. These hurdles must be addressed for stylometry to be usable in checking authorship of online messages such as emails, text messages, or twitter feeds. In this paper, we pose some steps toward achieving that goal by proposing a supervised learning technique combined with n-gram analysis for authorship verification in short texts. Experimental evaluation based on the Enron email dataset involving 87 authors yields very promising results consisting of an Equal Error Rate (EER) of 14.35% for message blocks of 500 characters.