An Information Theoretic Clustering Approach for Unveiling Authorship Affinities in Shakespearean Era Plays and Poems

Arefin, Ahmed Shamsul; Vimieiro, Renato; Riveros, Carlos; Craig, Hugh; Moscato, Pablo

doi:10.1371/journal.pone.0111445

Cited by 15 publications

(6 citation statements)

References 30 publications

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“…The two binary classes in this data set are plays (202) and poems (54). The “frequency of use” of 220 functional words has been extracted from a cohort of 66 907 words previously analyzed by Arefin et al The observed frequencies in the different works of these 220 functional words are used as features. The goal is to identify “a subset of functional words” that can group the works into the two classes: plays and poems.…”

Section: Computational Resultsmentioning

confidence: 99%

“…Univariate filter methods start by individually ranking each feature by using a statistical test or a predefined criterion and then using some ad hoc method to select the best‐ranked features . Examples of univariate filter–based feature selection methods can be found in the works of Arefin et al and Vergara and Estévez . Understandably, such methods do not consider the pairwise correlation between feature values across the set of samples.…”

Section: Introductionmentioning

confidence: 99%

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An adaptive memetic algorithm for feature selection using proximity graphs

Zaher

Berretta

Noman

et al. 2018

Computational Intelligence

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We propose a multivariate feature selection method that uses proximity graphs for assessing the quality of feature subsets. Initially, a complete graph is built, where nodes are the samples, and edge weights are calculated considering only the selected features. Next, a proximity graph is constructed on the basis of these weights and different fitness functions, calculated over the proximity graph, to evaluate the quality of the selected feature set. We propose an iterative methodology on the basis of a memetic algorithm for exploring the space of possible feature subsets aimed at maximizing a quality score. We designed multiple local search strategies, and we used an adaptive strategy for automatic balancing between the global and local search components of the memetic algorithm. The computational experiments were carried out using four well‐known data sets. We investigate the suitability of three different proximity graphs (minimum spanning tree, k‐nearest neighbors, and relative neighborhood graph) for the proposed approach. The selected features have been evaluated using a total of 49 classification methods from an open‐source data mining and machine learning package (WEKA). The computational results show that the proposed adaptive memetic algorithm can perform better than traditional genetic algorithms in finding more useful feature sets. Finally, we establish the competitiveness of our approach by comparing it with other well‐known feature selection methods.

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Section: Computational Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

An adaptive memetic algorithm for feature selection using proximity graphs

Zaher

Berretta

Noman

et al. 2018

Computational Intelligence

Self Cite

View full text Add to dashboard Cite

show abstract

“…Vickers ( 2011 ) uses a tri-gram, or n-gram, approach, while (Hirsch and Craig, 2014 ) use function word frequency. They also use methods based on the Information Theoretic measure Jensen-Shannon divergence (JSD), and unsupervised graph partitioning clustering algorithms (Arefin et al, 2014 ). There are other techniques used in this period of Shakespearean analysis, including simple function words (Matthews and Merriam, 1993 ; Merriam and Matthews, 1994 ) and word adjacency networks (WANs) (Segarra et al, 2017 ), or looking at rare and unique phrases (Swaim, 2017 ).…”

Section: Introductionmentioning

confidence: 99%

Using Shakespeare's Sotto Voce to Determine True Identity From Text

2018

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Little is known of the private life of William Shakespeare, but he is famous for his collection of plays and poems, even though many of the works attributed to him were published anonymously. Determining the identity of Shakespeare has fascinated scholars for 400 years, and four significant figures in English literary history have been suggested as likely alternatives to Shakespeare for some disputed works: Bacon, de Vere, Stanley, and Marlowe. A myriad of computational and statistical tools and techniques have been used to determine the true authorship of his works. Many of these techniques rely on basic statistical correlations, word counts, collocated word groups, or keyword density, but no one method has been decided on. We suggest that an alternative technique that uses word semantics to draw on personality can provide an accurate profile of a person. To test this claim, we analyse the works of Shakespeare, Christopher Marlowe, and Elizabeth Cary. We use Word Accumulation Curves, Hierarchical Clustering overlays, Principal Component Analysis, and Linear Discriminant Analysis techniques in combination with RPAS, a multi-faceted text analysis approach that draws on a writer's personality, or self to identify subtle characteristics within a person's writing style. Here we find that RPAS can separate the known authored works of Shakespeare from Marlowe and Cary. Further, it separates their contested works, works suspected of being written by others. While few authorship identification techniques identify self from the way a person writes, we demonstrate that these stylistic characteristics are as applicable 400 years ago as they are today and have the potential to be used within cyberspace for law enforcement purposes.

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“…Garrard et al (2005) were also instrumental in highlighting Alzheimer's disease through changes in writing and used a different approach which included some other elements of language (nouns, verbs, adverbs and adjectives and function words, e.g., conjunctions, and pronouns) to create word lists. As Arefin et al (2014) and Ferguson et al (2014) point out: the study of the subtle language changes over the lifespan of well-known writers (Lancashire, 2010), including Iris Murdoch and Agatha Christie (e.g. Garrard et al, 2005;Van Velzen & Garrard, 2008;Lancashire & Hirst, 2009;Le, 2010;Le et al, 2011) and political figures (Garrard, 2009) has highlighted that Alzheimer's disease may be apparent years or even decades before anyone becomes aware of any symptoms of cognitive deterioration.…”

Section: Introductionmentioning

confidence: 99%

The Impact of Depression and Apathy on Sensory Language

Kernot¹,

Bossomaier²,

Bradbury³

2017

OJML

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The debate that language strongly influences thought is equally met by those who suggest language does not influence thought. While historically, the ability to communicate with words was believed to be intimately tied to an ability to form thoughts, we would argue that thought and language are linked together through our sensory and motor systems and severely impacted by depression and apathy. We test this by conducting parts of speech analysis from the comparative longitudinal studies of two highly creative and prolific writers, where one is diagnosed with Alzheimer's disease (AD), and the other lives a long and healthy life. We calculate function and contents word ratios, measure lexical repetition, and the use of sensory-based words in textual language to test for depression and apathy in AD which is supported by MannWhitney U-Testing and Principal Component Analysis. Our results support the hypothesis that thought and language are impacted by depression and apathy and revealed in a person's writing style 12 years before a formal diagnosis of Alzheimer's disease presents. We find higher lexical repetition in language 12 years prior to one author being diagnosed with AD while not apparent in the other. We identify low olfactory word use and also find that an increased use of sensory-based adjectives might be a sign of the early onset of Alzheimer's disease.

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An Information Theoretic Clustering Approach for Unveiling Authorship Affinities in Shakespearean Era Plays and Poems

Cited by 15 publications

References 30 publications

An adaptive memetic algorithm for feature selection using proximity graphs

An adaptive memetic algorithm for feature selection using proximity graphs

Using Shakespeare's Sotto Voce to Determine True Identity From Text

The Impact of Depression and Apathy on Sensory Language

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