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\"How much of ourselves do we disclose when we speak or write? A person's accent may reveal, for example, whether they hail from Australia, or Ireland, or Mississippi. But it's not just where we were born-we divulge all sorts of information about ourselves and our identity through language. Level of education, gender, age, and even aspects of our personality can all be reliably determined by our vocabulary and grammar. To those who know what to look for, we give ourselves away every time we open our mouths or tap on a keyboard. But how unique is a person's linguistic identity? Can language be used to identify a specific person? To identify-or to exonerate-a murder suspect? To determine who authored a particular book? The answer to all these questions is yes. Forensic and computational linguists have developed methods that allow linguistic fingerprinting to be used in law enforcement. Similar techniques are used by literary scholars to identify the authors of anonymous or contested works of literature. Many people have heard that linguistic analysis helped to catch the Unabomber, or to unmask an anonymous editorialist-but how is it done? Linguistic Fingerprints will explain how these methods were developed and how they are used to solve forensic and literary mysteries. But these techniques aren't perfect, and the book will also include some cautionary tales about mistaken linguistic identity\"-- Provided by publisher.

This article reports a stylometric study of contemporary French prose from the second half of the 20th century by authors from Europe and Francophone Africa. We test whether classical stylometry, long effective in authorship attribution, can also capture collective properties of large corpora – specifically author gender and cultural origin. Results show that, in fiction, gender detection is highly unreliable: skilled writers can convincingly adopt diverse voices regardless of sociological profile, whereas the same methods often succeed on non-fiction by users (blogs, emails, social media). Likewise, in French prose, analyses based on short lists of neutral function words fail to discriminate European from African authors. Clear separation appears only when long n-gram features are used, which encode culturally inflected vocabulary and contexts. We discuss methodological implications for stylometry beyond attribution.

This paper presents early results of a full-text and metadata study of translations of French prose and epic poetry contained in the Jagiellonian Corpus of Writing in Polish. It combines distant reading with stylometry to shed new light on trends and patterns and evolution in the history of Polish translation of French literature.

The authorship of the French novel L’enfant du bordel (1800) remains contested, with attributions ranging from lesser-known writer Pigault-Lebrun to revolutionary and author Mirabeau. To clarify its authorship, we conducted multiple stylometric analyses using a corpus of Eighteenth-century French novels. Comparing the distance matrix and the Ward’s linkage dendrogram reveals discrepancies in the authorship hypotheses which were examined using the General Imposters method. A knowledge graph on French Eighteenth century literature was further used to identify potentially interfering influences on similarity, like thematic relations or narrative form. Based on the stylometric results and the analysis of the knowledge graph, we conclude that the most probable author is Pigault-Lebrun.

The authenticity of the Additamentum Aldinum (Sil. Pun. 8.144–223) has long been a matter of debate. While many scholars have expressed doubts that it is by Silius and suggest rather that it is from the hands of a skilful humanist, it has not, up to this time, been possible to provide solid evidence to support their intuition. This paper not only re-examines the standard arguments for and against authenticity but brings the latest computational stylometric techniques to bear on the question. These analyses reveal that the style of the Additamentum differs in statistically significant terms from the rest of Silius’ Punica.1

This study systematically compares four prominent Chinese translations of Plato’s Republic against two authoritative English benchmark translations, addressing a critical gap in existing Platonic scholarship: the lack of objective comparative analysis of its diverse Chinese versions. Using a three-tiered computational stylistic framework comprising macro-stylistic positioning, micro-level syntactic and lexical features, and cognitive-linguistic profiling via LIWC categories, we analyzed a purpose-built parallel corpus of 935,861 tokens. The corpus comprises four influential Chinese translations (Gu Shouguan 2010, Guo Binhe 1986, He Xiangdi 2021, Xie Shanyuan 2016) and two English benchmarks (Allan Bloom 1968, C. D. C. Reeve 2004). Significant stylistic divergences emerged among the Chinese versions and in contrast to the English texts. Chinese translations consistently exhibit a pronounced tendency toward explicitation, marked by significantly higher frequencies of cognitive process words (13.7%–16.4% vs. 11.2%–12.7% in English versions, d = −1.75, p < .001) and elevated frequencies of logical connectives, particularly result and contrast markers. Notable variations in syntactic complexity were also found, ranging from Guo Binhe’s concise style (17.985 tokens per sentence) to Gu Shouguan’s elaborate style (27.419 tokens per sentence), with substantial variation among Chinese translations (η 2 = 0.18–0.48). These findings underscore that the Chinese Republic translations are not mere linguistic variants but unique intellectual projects shaped by deliberate interpretive strategies and cultural contexts, highlighting translation’s active role in philosophical re-creation and re-localization. One Book, Four Different Voices: Using Computer Analysis to Uncover the Stylistic Fingerprints of Chinese Translations of Plato’s Republic Plato’s Republic is a cornerstone of Western philosophy, but how does it read in another language? In China, students and scholars face a “paradox of choice” with over ten different translations available. This study uses computer-based analysis to compare four influential Chinese translations by Gu Shouguan 2010, Guo Binhe 1986, He Xiangdi 2021, and Xie Shanyuan 2016, against two English benchmark versions. We analyzed nearly 936,000 words, examining sentence length, word types, and how translators handle key philosophical terms. The results reveal notable variations. Gu Shouguan’s version tends to use extremely long, complex sentences averaging over 27 words, aiming for a formal style. In contrast, Guo Binhe’s translation tends to use shorter sentences averaging about 18 words, making Plato’s ideas more accessible. The Chinese translations tend to make Plato’s logical arguments more explicit than the English versions, often adding connecting words like “therefore” and “because” to guide readers. They also tend to use more words expressing contrast and result, while English versions rely more on words signaling reasons. These stylistic choices appear to reflect the translators’ unique backgrounds, the historical eras spanning from 1986 to 2021, and their different goals. This research suggests that a single classic can become multiple, distinct works in translation, each offering a different window into Plato’s thought for Chinese readers.

Online Social Media (OSM) have been substantially transforming the process of spreading news, improving its speed, and reducing barriers toward reaching out to a broad audience. However, OSM are very limited in providing mechanisms to check the credibility of news propagated through their structure. The majority of studies on automatic fake news detection are restricted to English documents, with few works evaluating other languages, and none comparing language-independent characteristics. Moreover, the spreading of deceptive news tends to be a worldwide problem; therefore, this work evaluates textual features that are not tied to a specific language when describing textual data for detecting news. Corpora of news written in American English, Brazilian Portuguese, and Spanish were explored to study complexity, stylometric, and psychological text features. The extracted features support the detection of fake, legitimate, and satirical news. We compared four machine learning algorithms (k-Nearest Neighbors (k-NN), Support Vector Machine (SVM), Random Forest (RF), and Extreme Gradient Boosting (XGB)) to induce the detection model. Results show our proposed language-independent features are successful in describing fake, satirical, and legitimate news across three different languages, with an average detection accuracy of 85.3% with RF.

Fake news is being generated in different languages, yet existing studies are dominated by English news. The analysis of fake news content has focused on lexical and stylometric features, giving little attention to semantic features. A few studies involving semantic features have either used them as the inputs to classifiers with no interpretations, or treated them in isolation. This research aims to investigate both thematic and emotional characteristics of fake news at different levels and compare them between different languages for the first time. It extends a state-of-the-art topic modeling technique to extract news topics and introduces a divergence measure to assess the importance of thematic characteristics for identifying fake news. We further examine associations of the thematic and emotional characteristics of fake news. The empirical findings have implications for developing both general and language-specific countermeasures for fake news.

Authorship attribution is one of the fields that has benefited most from the recent developments in stylometry. However, there are no general guidelines on the parameters to be used for reliable authorship attribution, since the performance of stylometric analysis is highly influenced by the language and length of the texts, as well as the composition of the corpus. This paper aims to test the performance of the stylo package on two Romanian corpora of short texts, one of them homogeneous and the other heterogeneous. The overarching objective of our research is to propose some guidelines for authorship attribution tasks on Romanian short literary texts and see to what extent the corpus composition influences the results. Likewise, by comparing the results obtained with the intuitive stylo package to those obtained with considerably more sophisticated digital tools, we aim to point to the on-the-shelf feasibility of reliable stylometric analysis even in less-resourced languages.

Literature is a form of expression whose temporal structure, both in content and style, provides a historical record of the evolution of culture. In this work we take on a quantitative analysis of literary style and conduct the first large-scale temporal stylometric study of literature by using the vast holdings in the Project Gutenberg Digital Library corpus. We find temporal stylistic localization among authors through the analysis of the similarity structure in feature vectors derived from content-free word usage, nonhomogeneous decay rates of stylistic influence, and an accelerating rate of decay of influence among modern authors. Within a given time period we also find evidence for stylistic coherence with a given literary topic, such that writers in different fields adopt different literary styles. This study gives quantitative support to the notion of a literary \"style of a time\" with a strong trend toward increasingly contemporaneous stylistic influence.