An innovative framework for supporting content-based authorship identification and analysis in social media networks

Pub Date : 2024-03-26 DOI:10.1093/jigpal/jzae020
José Gaviria de la Puerta, Iker Pastor-López, Alberto Tellaeche, Borja Sanz, Hugo Sanjurjo-González, Alfredo Cuzzocrea, Pablo G Bringas
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Abstract

Content-based authorship identification is an emerging research problem in online social media networks, due to a wide collection of issues ranging from security to privacy preservation, from radicalization to defamation detection, and so forth. Indeed, this research has attracted a relevant amount of attention from the research community during the past years. The general problem becomes harder when we consider the additional constraint of identifying the same false profile over different social media networks, under obvious considerations. Inspired by this emerging research challenge, in this paper we propose and experimentally assess an innovative framework for supporting content-based authorship identification and analysis in social media networks.
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支持社交媒体网络中基于内容的作者身份识别和分析的创新框架
基于内容的作者身份识别是在线社交媒体网络中一个新兴的研究问题,它涉及从安全到隐私保护、从激进化到诽谤检测等一系列问题。事实上,这项研究在过去几年里已经引起了研究界的广泛关注。在显而易见的考虑因素下,如果我们考虑到在不同社交媒体网络中识别相同虚假资料的额外约束,一般问题就会变得更加困难。受这一新兴研究挑战的启发,我们在本文中提出了一个创新框架,用于支持社交媒体网络中基于内容的作者身份识别和分析,并进行了实验评估。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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