This paper is our attempt at answering a twofold question covering the areas of ethics and authorship analysis solutions. Firstly, since the methods used for performing authorship analysis imply that an author can be recognized by the content he or she creates, we were interested in finding out whether it would be possible for an author identification system to correctly attribute works to authors if in the course of years they have undergone a major psychological transition. Secondly – and from the point of view of the evolution of an author’s ethical values – we checked what it would mean if the authorship attribution system encounters difficulties in detecting single authorship. We set out to answer those questions through performing a binary authorship analysis task using a text classifier based on a pre-trained transformer model and a baseline method relying on conventional similarity metrics. For the test set, we chose several works of Arata Osada, a Japanese educator and specialist in the history of education, with half of them being books written before the Second World War and another half in the 1950s, in between which the author underwent a transformation in terms of political opinions. As a result, we were able to confirm that in the case of texts authored by Arata Osada in a time span of more than 10 years, while the classification accuracy drops by a large margin and is substantially lower than for texts by other non-fiction writers, confidence scores of the predictions remain at a similar level as in the case of a shorter time span, indicating that the classifier was in many instances tricked into deciding that texts written by Arata Osada over a time span of multiple years were actually written by two different people, which in turn leads us to believe that such a change can affect authorship analysis, and that historical events have great impact on a person’s ethical outlook as expressed in their writings.

本文试图回答一个涉及伦理和作者身份分析解决方案领域的双重问题。首先，由于用于执行作者身份分析的方法意味着作者可以通过他或她创建的内容来识别，我们有兴趣找出作者识别系统是否有可能正确地将作品归于作者，如果在多年来，他们经历了重大的心理转变。其次——从作者道德价值观演变的角度来看——我们检查了如果作者归属系统在检测单一作者身份时遇到困难会意味着什么。我们开始通过使用基于预训练转换器模型的文本分类器和依赖于传统相似性度量的基线方法执行二进制作者分析任务来回答这些问题。对于测试集，我们选择了日本教育家、教育史专家小佐田新 (Arata Osada) 的几部作品，其中一半是二战前写的书，另一半是 1950 年代的书，其中作者经历了政治观点的转变。结果，我们能够确认，在 Arata Osada 创作的时间跨度超过 10 年的文本中，分类准确率大幅下降，远低于其他非小说类的文本作家，