Search

INTRODUCTION On September 5, 2018, the New York Times published what might be, according to one commentator, "the most significant and consequential op-ed ever published." (1) The article, purportedly authored [...]

In this paper, we present preliminary results on how an individual's writing style persists even across languages. In other words, what aspects of an individual's writing will persist irrespective of the language in which he or she writes? We argue that cognitive and social traits are likely to persist and demonstrate this by two separate analyses of bilingual corpora using the same individuals. We show that for various measures of linguistic complexity (which we consider to be a cognitive variable) and participation in specific social conventions (a social one), the correlation between scores on the two languages studied is significantly higher than would be expected by chance. We argue that this type of correlation may permit cross-linguistic authorship attribution. [ABSTRACT FROM AUTHOR]

Authorship attribution is an important problem in text classification, with many applications and a substantial body of research activity. Among the research findings are that many different methods will work, including a number of methods that are superficially language‐independent (such as an analysis of the most common "words" or "character n‐grams" in a document). Since all languages have words (and all written languages have characters), this method could (in theory) work on any language. However, it is not clear that the methods that work best on, for example English, would also work best on other languages. It is not even clear that the same level of performance is achievable in different languages, even under identical conditions. Unfortunately, it is very difficult to achieve "identical conditions" in practice. A new corpus, developed by George Mikros, provides very tight controls not only for author but also for topic, thus enabling a direct comparison of performance levels between the two languages Greek and English. We compare a number of different methods head‐to‐head on this corpus, and show that, overall, performance on English is higher than performance on Greek, often highly significantly so. [ABSTRACT FROM AUTHOR]

'Authorship attribution', the problem of determining the author (or the author's attributes, such as gender, age, native language, or other characteristics) by examining the writing style of an unknown work, is an important problem in applied linguistics. The theory of authorship attribution is relatively straightforward: language is an underspecified system, and people can pick and choose among several different ways to describe the same thing. These choices, in turn, become habituated and can be identified as persistent patterns of an individual or group of writers. One important psycholinguistic underpinning to this solution is the universal existence (in natural languages) of so-called ''marker words'' or 'function words,'--little, closed-class words that do not carry much semantics but instead denote relationships between content words. Because these words are so lightly processed, writers/speakers can choose among many different near-synonymous forms, and implicitly express their identity in doing so. Do constructed languages have this same degree of near-synonymity? We present the results of a study of authorship attribution using an ad-hoc corpus of fanwritten documents in various constructed languages, and show that even artificial languages constructed for artistic purposes, such as Klingon, Na'vi, and Elvish, permit this type of analysis. This indicates that even constructed languages tend to be psycholinguistically plausible. [ABSTRACT FROM AUTHOR]