Close Reading with Computers: Genre Signals, Parts of Speech, and David Mitchell’s Cloud Atlas

David Mitchell’s Cloud Atlas (2004) contains six different generic registers. This article is the first to explore computationally the linguistic mechanisms that create these genre effects. Authorship attribution techniques incorrectly cluster the chapters of Cloud Atlas as distinct ‘authors’ using anything above the nineteen most-common words. This has implications for understandings of literary style and authorship. The seafaring parts of Mitchell’s novel, however, do not correlate with the writings of Herman Melville using Burrows’s delta method. Part-of-speech trigram visualization and analysis reveals the unique present-tense linguistic phrasings (NNP NNP VBZ and NNP VBZ DT) that lend pace to the Luisa Rey section of the novel

Authorship Verification

In recent years, stylometry, the study of linguistic style, has become more prominent in security and privacy applications involving written language, mostly in digital and online domains. Although literature is abundant with computational stylometry research, the field of authorship verification is relatively unexplored. Authorship verification is the binary semi-open-world problem of determining whether a document is written by a given author or not. A key component in authorship verification techniques is confidence measurement, on which verification decisions are based, expressed by acceptance thresholds selected and tuned per need. This thesis demonstrates how utilization of confidence-based approaches in stylometric applications, and their combination with traditional approaches, can benefit classification accuracy, and allow new domains and problems to be analyzed. We start by motivating the usage of authorship verification approaches with two stylometric applications: native-language identification from non-native text and active linguistic user authentication. Next, we introduce the Classify-Verify algorithm, which integrates classification with binary verification, applied to several stylometric problems. Classify-Verify is proposed as an open-world alternative to restricted closed-world attribution methods, and is shown effective in dealing with possibly missing candidate authors by thwarting misclassifications, coping with various domains and scales, and even adversarial authors who try to fool the classifier.Ph.D., Computer Science -- Drexel University, 201

A Machine Learning Approach for Plagiarism Detection

Plagiarism detection is gaining increasing importance due to requirements for integrity in education. The existing research has investigated the problem of plagrarim detection with a varying degree of success. The literature revealed that there are two main methods for detecting plagiarism, namely extrinsic and intrinsic. This thesis has developed two novel approaches to address both of these methods. Firstly a novel extrinsic method for detecting plagiarism is proposed. The method is based on four well-known techniques namely Bag of Words (BOW), Latent Semantic Analysis (LSA), Stylometry and Support Vector Machines (SVM). The LSA application was fine-tuned to take in the stylometric features (most common words) in order to characterise the document authorship as described in chapter 4. The results revealed that LSA based stylometry has outperformed the traditional LSA application. Support vector machine based algorithms were used to perform the classification procedure in order to predict which author has written a particular book being tested. The proposed method has successfully addressed the limitations of semantic characteristics and identified the document source by assigning the book being tested to the right author in most cases. Secondly, the intrinsic detection method has relied on the use of the statistical properties of the most common words. LSA was applied in this method to a group of most common words (MCWs) to extract their usage patterns based on the transitivity property of LSA. The feature sets of the intrinsic model were based on the frequency of the most common words, their relative frequencies in series, and the deviation of these frequencies across all books for a particular author. The Intrinsic method aims to generate a model of author “style” by revealing a set of certain features of authorship. The model’s generation procedure focuses on just one author as an attempt to summarise aspects of an author’s style in a definitive and clear-cut manner. The thesis has also proposed a novel experimental methodology for testing the performance of both extrinsic and intrinsic methods for plagiarism detection. This methodology relies upon the CEN (Corpus of English Novels) training dataset, but divides that dataset up into training and test datasets in a novel manner. Both approaches have been evaluated using the well-known leave-one-out-cross-validation method. Results indicated that by integrating deep analysis (LSA) and Stylometric analysis, hidden changes can be identified whether or not a reference collection exists

A computational academic integrity framework

L'abast creixent i la naturalesa canviant dels programes acadèmics constitueixen un repte per a la integritat dels protocols tradicionals de proves i exàmens. L'objectiu d¿aquesta tesi és introduir una alternativa als enfocaments tradicionals d'integritat acadèmica, per a cobrir la bretxa del buit de l'anonimat i donar la possibilitat als instructors i administradors acadèmics de fer servir nous mitjans que permetin mantenir la integritat acadèmica i promoguin la responsabilitat, accessibilitat i eficiència, a més de preservar la privadesa i minimitzin la interrupció en el procés d'aprenentatge. Aquest treball té com a objectiu començar un canvi de paradigma en les pràctiques d'integritat acadèmica. La recerca en l'àrea de la identitat de l'estudiant i la garantia de l'autoria són importants perquè la concessió de crèdits d'estudi a entitats no verificades és perjudicial per a la credibilitat institucional i la seguretat pública. Aquesta tesi es basa en la noció que la identitat de l'alumne es compon de dues capes diferents, física i de comportament, en les quals tant els criteris d'identitat com els d'autoria han de ser confirmats per a mantenir un nivell raonable d'integritat acadèmica. Per a això, aquesta tesi s'organitza en tres seccions, cadascuna de les quals aborda el problema des d'una de les perspectives següents: (a) teòrica, (b) empírica i (c) pragmàtica.El creciente alcance y la naturaleza cambiante de los programas académicos constituyen un reto para la integridad de los protocolos tradicionales de pruebas y exámenes. El objetivo de esta tesis es introducir una alternativa a los enfoques tradicionales de integridad académica, para cubrir la brecha del vacío anonimato y dar la posibilidad a los instructores y administradores académicos de usar nuevos medios que permitan mantener la integridad académica y promuevan la responsabilidad, accesibilidad y eficiencia, además de preservar la privacidad y minimizar la interrupción en el proceso de aprendizaje. Este trabajo tiene como objetivo iniciar un cambio de paradigma en las prácticas de integridad académica. La investigación en el área de la identidad del estudiante y la garantía de la autoría son importantes porque la concesión de créditos de estudio a entidades no verificadas es perjudicial para la credibilidad institucional y la seguridad pública. Esta tesis se basa en la noción de que la identidad del alumno se compone de dos capas distintas, física y de comportamiento, en las que tanto los criterios de identidad como los de autoría deben ser confirmados para mantener un nivel razonable de integridad académica. Para ello, esta tesis se organiza en tres secciones, cada una de las cuales aborda el problema desde una de las siguientes perspectivas: (a) teórica, (b) empírica y (c) pragmática.The growing scope and changing nature of academic programmes provide a challenge to the integrity of traditional testing and examination protocols. The aim of this thesis is to introduce an alternative to the traditional approaches to academic integrity, bridging the anonymity gap and empowering instructors and academic administrators with new ways of maintaining academic integrity that preserve privacy, minimize disruption to the learning process, and promote accountability, accessibility and efficiency. This work aims to initiate a paradigm shift in academic integrity practices. Research in the area of learner identity and authorship assurance is important because the award of course credits to unverified entities is detrimental to institutional credibility and public safety. This thesis builds upon the notion of learner identity consisting of two distinct layers (a physical layer and a behavioural layer), where the criteria of identity and authorship must both be confirmed to maintain a reasonable level of academic integrity. To pursue this goal in organized fashion, this thesis has the following three sections: (a) theoretical, (b) empirical, and (c) pragmatic

A Computational Academic Integrity Framework

L'abast creixent i la naturalesa canviant dels programes acadèmics constitueixen un repte per a la integritat dels protocols tradicionals de proves i exàmens. L'objectiu d'aquesta tesi és introduir una alternativa als enfocaments tradicionals d'integritat acadèmica, per a cobrir la bretxa del buit de l'anonimat i donar la possibilitat als instructors i administradors acadèmics de fer servir nous mitjans que permetin mantenir la integritat acadèmica i promoguin la responsabilitat, accessibilitat i eficiència, a més de preservar la privadesa i minimitzin la interrupció en el procés d'aprenentatge. Aquest treball té com a objectiu començar un canvi de paradigma en les pràctiques d'integritat acadèmica. La recerca en l'àrea de la identitat de l'estudiant i la garantia de l'autoria són importants perquè la concessió de crèdits d'estudi a entitats no verificades és perjudicial per a la credibilitat institucional i la seguretat pública. Aquesta tesi es basa en la noció que la identitat de l'alumne es compon de dues capes diferents, física i de comportament, en les quals tant els criteris d'identitat com els d'autoria han de ser confirmats per a mantenir un nivell raonable d'integritat acadèmica. Per a això, aquesta tesi s'organitza en tres seccions, cadascuna de les quals aborda el problema des d'una de les perspectives següents: (a) teòrica, (b) empírica i (c) pragmàtica.El creciente alcance y la naturaleza cambiante de los programas académicos constituyen un reto para la integridad de los protocolos tradicionales de pruebas y exámenes. El objetivo de esta tesis es introducir una alternativa a los enfoques tradicionales de integridad académica, para cubrir la brecha del vacío anonimato y dar la posibilidad a los instructores y administradores académicos de usar nuevos medios que permitan mantener la integridad académica y promuevan la responsabilidad, accesibilidad y eficiencia, además de preservar la privacidad y minimizar la interrupción en el proceso de aprendizaje. Este trabajo tiene como objetivo iniciar un cambio de paradigma en las prácticas de integridad académica. La investigación en el área de la identidad del estudiante y la garantía de la autoría son importantes porque la concesión de créditos de estudio a entidades no verificadas es perjudicial para la credibilidad institucional y la seguridad pública. Esta tesis se basa en la noción de que la identidad del alumno se compone de dos capas distintas, física y de comportamiento, en las que tanto los criterios de identidad como los de autoría deben ser confirmados para mantener un nivel razonable de integridad académica. Para ello, esta tesis se organiza en tres secciones, cada una de las cuales aborda el problema desde una de las siguientes perspectivas: (a) teórica, (b) empírica y (c) pragmática.The growing scope and changing nature of academic programmes provide a challenge to the integrity of traditional testing and examination protocols. The aim of this thesis is to introduce an alternative to the traditional approaches to academic integrity, bridging the anonymity gap and empowering instructors and academic administrators with new ways of maintaining academic integrity that preserve privacy, minimize disruption to the learning process, and promote accountability, accessibility and efficiency. This work aims to initiate a paradigm shift in academic integrity practices. Research in the area of learner identity and authorship assurance is important because the award of course credits to unverified entities is detrimental to institutional credibility and public safety. This thesis builds upon the notion of learner identity consisting of two distinct layers (a physical layer and a behavioural layer), where the criteria of identity and authorship must both be confirmed to maintain a reasonable level of academic integrity. To pursue this goal in organized fashion, this thesis has the following three sections: (a) theoretical, (b) empirical, and (c) pragmatic

From n-grams to n-sets: A Fuzzy-Logic-Based Approach to Shakespearian Authorship Attribution.

This thesis surveys the principles of Fuzzy Logic as they have been applied in the last three decades in the micro-electronic field and, in the context of resolving problems of authorship verification and attribution shows how these principles can assist with the detection of stylistic similarities or dissimilarities of an anonymous, disputed play to an author’s general or patterns-based known style. The main stylistic markers are the counts of semantic sets of 100 individual words-tokens and an index of counts of these words’ frequencies (a cosine index), as found in the first extract of approximately 10,000 words of each of 27 well attributed Shakespearian plays. Based on these markers, their geometrical representation, fuzzy modelling and on thee ground of Set Theory and Boolean Algebra, in the core part of this thesis three Mamdani (Type-1) genre-based Fuzzy Expert Systems were built for the detection of degrees (measured on a scale from 0 to 1) of Shakespearianness of disputed and, probably, co-authored plays of the early modern English period. Each of these three expert systems is composed of seven input and two output variables that are associated through a set of approximately 30 to 40 rules. There is a detailed description of the properties of the three expert systems’ inference mechanisms and the various experimentation phases. There is also an indicative graphical analysis of the phases of the experimentation and a thorough explanation of terms, such as partial truths membership, approximate reasoning and output centroids on an X-axis of a two-dimensional space. Throughout the thesis there is an extensive demonstration of various Fuzzy Logic techniques, including Sugeno-ANFIS (adaptive neuro-fuzzy inference system), with which the style of Shakespeare can be modelled in order to compare it with well attributed plays of other authors or plays that are not included in the strict Shakespearian canon of the selected 27 well-attributed, sole authored plays. In addition, other relevant issues of stylometric concern are discussed, such as the investigation and classification of known ‘problem’ and disputed plays through holistic classifiers (irrespective of genre). The results of the experimentation advocate the use of this novel, automated and computer simulation-based method of classification in the stylometric field for various purposes. In fact, the three models have succeeded in detecting the low Shakespearianness of non Shakespearian plays and the results they provided for anonymous, disputed plays are in conformance with the general evidence of historical scholarship. Therefore, the original contribution of this thesis is to define fully functional automated fuzzy classifiers of Shakespearianness. The result of this discovery is that we now know that the principles of fuzzy modelling can be applied for the creation of Fuzzy Expert Stylistic Classifiers and the concomitant detection of degrees of similarity of a play under scrutiny with the general or patterns-based known style of a specific author (in our case, Shakespeare). Furthermore, this thesis shows that, given certain premises, counts of words’ frequencies and counts of semantic sets of words can be employed satisfactorily for stylistic discrimination

Adversarial Stylometry in the Wild: Transferable Lexical Substitution Attacks on Author Profiling

Written language contains stylistic cues that can be exploited to automatically infer a variety of potentially sensitive author information. Adversarial stylometry intends to attack such models by rewriting an author's text. Our research proposes several components to facilitate deployment of these adversarial attacks in the wild, where neither data nor target models are accessible. We introduce a transformer-based extension of a lexical replacement attack, and show it achieves high transferability when trained on a weakly labeled corpus -- decreasing target model performance below chance. While not completely inconspicuous, our more successful attacks also prove notably less detectable by humans. Our framework therefore provides a promising direction for future privacy-preserving adversarial attacks.Comment: Accepted to EACL 202