A series of social media posts signed under the pseudonym "Q", started a movement known as QAnon, which led some of its most radical supporters to violent and illegal actions. To identify the person(s) behind Q, we evaluate the coincidence between the linguistic properties of the texts written by Q and to those written by a list of suspects provided by journalistic investigation. To identify the authors of these posts, serious challenges have to be addressed. The "Q drops" are very short texts, written in a way that constitute a sort of literary genre in itself, with very peculiar features of style. These texts might have been written by different authors, whose other writings are often hard to find. After an online ethnology of the movement, necessary to collect enough material written by these thirteen potential authors, we use supervised machine learning to build stylistic profiles for each of them. We then performed a rolling analysis on Q's writings, to see if any of those linguistic profiles match the so-called 'QDrops' in part or entirety. We conclude that two different individuals, Paul F. and Ron W., are the closest match to Q's linguistic signature, and they could have successively written Q's texts. These potential authors are not high-ranked personality from the U.S. administration, but rather social media activists.
翻译:以假名“ Q” 签名的一系列社交媒体文章开始了一个名为“ QAnon” 的运动,它导致一些最激进的支持者采取暴力和非法行动。为了识别Q背后的人,我们评估Q所写文本的语言性质与新闻调查提供的嫌疑人名单所写文本之间的巧合。为了识别这些文章的作者,必须解决严峻的挑战。“ Q drops” 是非常简短的文本, 本身就是一种文学风格, 具有非常特殊的特点。 这些文本可能是由不同的作者写的, 而这些作者的其他著作往往很难找到。 在对Q所写文本进行在线族裔学之后,为了收集这13个潜在作者所写的足够材料,我们用受监督的机器学习来为这些文章中的每一个人建立文体谱特征。 然后我们对Q的著作进行滚动分析,看看其中的任何语言特征是否与所谓的“ Qdrops” 部分或全部相匹配。我们的结论是,两个不同的个人,Paul F. 和Ron W.</s>