The diary of a public man: a case study in traditional and non-traditional authorship attribution

Holmes, David; Crofts, Daniel W.

doi:10.1093/llc/fqq005

Cited by 26 publications

(21 citation statements)

References 11 publications

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“…Many studies since that of Mosteller and Wallace have shown the efficacy of function words for authorship attribution in different scenarios (Morton 1978;Burrows 1987;Karlgren & Cutting 1994;Merriam & Matthews 1994;Kessler et al 1997;Argamon et al 1998;Holmes 1998;de Vel et al 2001;Holmes et al 2001aHolmes et al , 2001bBaayen et al 2002;Binongo 2003;Juola & Baayen 2003;Zhao & Zobel 2005;Argamon & Levitan 2005;Koppel et al 2005Koppel et al , 2006a, confirming the hypothesis that different authors tend to have different characteristic patterns of function word use.…”

Section: Function Wordsmentioning

confidence: 82%

Computational methods in authorship attribution

Koppel

Schler

Argamon

2008

J. Am. Soc. Inf. Sci.

453

278

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Statistical authorship attribution has a long history, culminating in the use of modern machine learning classification methods. Nevertheless, most of this work suffers from the limitation of assuming a small closed set of candidate authors and essentially unlimited training text for each. Real-life authorship attribution problems, however, typically fall short of this ideal. Thus, following detailed discussion of previous work, three scenarios are considered here for which solutions to the basic attribution problem are inadequate. In the first variant, the profiling problem, there is no candidate set at all; in this case, the challenge is to provide as much demographic or psychological information as possible about the author. In the second variant, the needle-in-a-haystack problem, there are many thousands of candidates for each of whom we might have a very limited writing sample.In the third variant, the verification problem, there is no closed candidate set but there is one suspect; in this case, the challenge is to determine if the suspect is or is not the author. For each variant, it is shown how machine learning methods can be adapted to handle the special challenges of that variant.

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Section: Function Wordsmentioning

confidence: 82%

Computational methods in authorship attribution

Koppel

Schler

Argamon

2008

J. Am. Soc. Inf. Sci.

453

278

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“…Standard applications of stylometry include dating literary works and resolving questions of attribution (26)(27)(28)(29)(30). Both ad hoc stylometric analysis and supervised machine learning with stylometric features have proven successful for such applications (31)(32)(33), including for cases in Latin literature (34).…”

Section: Significancementioning

confidence: 99%

Quantitative criticism of literary relationships

Dexter

Katz

Tripuraneni

et al. 2017

Proc. Natl. Acad. Sci. U.S.A.

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Authors often convey meaning by referring to or imitating prior works of literature, a process that creates complex networks of literary relationships ("intertextuality") and contributes to cultural evolution. In this paper, we use techniques from stylometry and machine learning to address subjective literary critical questions about Latin literature, a corpus marked by an extraordinary concentration of intertextuality. Our work, which we term "quantitative criticism," focuses on case studies involving two influential Roman authors, the playwright Seneca and the historian Livy. We find that four plays related to but distinct from Seneca's main writings are differentiated from the rest of the corpus by subtle but important stylistic features. We offer literary interpretations of the significance of these anomalies, providing quantitative data in support of hypotheses about the use of unusual formal features and the interplay between sound and meaning. The second part of the paper describes a machine-learning approach to the identification and analysis of citational material that Livy loosely appropriated from earlier sources. We extend our approach to map the stylistic topography of Latin prose, identifying the writings of Caesar and his near-contemporary Livy as an inflection point in the development of Latin prose style. In total, our results reflect the integration of computational and humanistic methods to investigate a diverse range of literary questions.authorship attribution | cultural evolution | intertextuality | machine learning | stylometry T he study of literature relies on mapping interactions between texts. Ancient Greek critics understood the tragedies of Aeschylus in part through their relation to Homeric epic, and ancient Roman commentators interpreted words and phrases in texts by citing parallels in other works. Much of literary criticism today rests on understanding these vast networks of intertextuality, which often have profound consequences for the meaning of both individual texts and larger groupings by genre or period (1). Through quantitative analysis of formal elements and their change over time, the study of intertextuality can shed light on the cultural evolution of literature (2).A central challenge in the study of intertextuality is its heterogeneous nature. Literary parallels differ widely in both similarity and scope (Fig. 1A). The relationship between the associated texts can range from obvious (direct quotation) to extremely subtle (artfully constructed indirect references, often referred to as allusions in literary study). Furthermore, parallels can operate on the level of individual words or phrases, short passages, or entire works and can involve verbal, syntactic, phonetic, or metrical features. As illustrated in Fig. 1A, intertexts can be of comparable similarity but very different scope; an adaptation of an entire work, for instance, can be thought of as a collection of many (local) allusions.In this paper, we focus on the quantitative characterization of intertextual rela...

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“…Instead of limiting ourselves to a single value we could apply a multivariate analysis to capture each author's discriminative stylistic features (Holmes & Crofts, 2010). The most important studies applicable here (Burrows, 1992;Binonga & Smith, 1999;Craig & Kinney, 2009) are those related to PCA (Lebart et al, 1998).…”

Section: Related Workmentioning

confidence: 99%

“…Holmes and Crofts (2010) suggested using 100 lemmas, Burrows (2002) between 40 and 150. After applying the PCA method using the R system (Crawley, 2007;Husson et al, 2011), we obtained the results shown in Figure 1.…”

Section: Principal Component Analysis and Nearest Neighbormentioning

confidence: 99%

Authorship Attribution: A Comparative Study of Three Text Corpora and Three Languages

Savoy

2012

Journal of Quantitative Linguistics

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The first objective of this paper is carry out three experiments intended to evaluate authorship attribution methods based on three test-collections available in three different languages (English, French, and German). In the first we represent and categorize 52 text excerpts written by nine authors and taken from 19th century English novels. In the second we work with 44 segments from French novels written by eleven authors, mostly from the 19th century. In the third we extract 59 German text excerpts from novels published mainly during the 19th and the beginning of the 20th century, written by 15 authors. The second objective is to analyse performance differences obtained when using word types or lemmas as text representations, and the third objective is to evaluate three authorship attribution schemes, the first of which uses principal component analysis (PCA), the second applies the Delta approach, and the third corresponds to a new authorship attribution method based on specific vocabulary. This concept is computed for a given text (or author profile) and then compared with the entire corpus. Based on this information, we show how a distance measure can be derived and by means of the nearest neighbor approach we suggest a simple and efficient authorship attribution scheme. Based on three test collections and using either word types or lemmas as features, we demonstrate that the suggested classification scheme performs better than the PCA method, and slightly better than the Delta approach.

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The diary of a public man: a case study in traditional and non-traditional authorship attribution

Cited by 26 publications

References 11 publications

Computational methods in authorship attribution

Computational methods in authorship attribution

Quantitative criticism of literary relationships

Authorship Attribution: A Comparative Study of Three Text Corpora and Three Languages

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