Plotting Poetry 3. Conference report

Plotting Poetry 3. Conference repor

Plotting Poetry: On mechanically enhanced reading, 5–7 October 2017, Basel, Switzerland

Plotting Poetry: On mechanically enhanced reading, 5–7 October 2017, Basel, Switzerlan

Computational Stylistics in Poetry, Prose, and Drama

The contributions in this edited volume approach poetry, narrative, and drama from the perspective of Computational Stylistics. They exemplify methods of computational textual analysis and explore the possibility of computational generation of literary texts. The volume presents a range of computational and Natural Language Processing applications to literary studies, such as motif detection, network analysis, machine learning, and deep learning

Need for narrative

What do consumers need from a narrative? How can videographers satisfy those needs? Through semi-structured interviews with 55 Eurostar passengers from 14 countries, this film documents how people define narratives, why they need them, and how they experience the effects of need for narrative. The adjoining commentary contributes to the development of videography as an attractive method by introducing the videographer’s perspective and elucidating key story elements that can help satisfy viewers’ needs for narrative. The suggested approach maintains the vivid quality of videography and respects its methodological rigour, while increasing its effectiveness in close alignment with a consumer society that visual communication increasingly permeates. As such, the commentary and the film jointly unveil videographers’ etic and viewers’ emic use and evaluation of the videographic method

Vyacheslav V. Ivanov (1929–2017) and his Studies in Prosody and Poetics

Vyacheslav V. Ivanov was an outstanding scholar who excelled in almost all disciplines related to linguistic and literary studies. This article analyses his accomplishments in the fields of prosody and poetics

The Bechdel Test and the Social Form of Character Networks

This essay describes the popular Bechdel Test—a measure of women’s dialogue in films—in terms of social network analysis within fictional narrative. It argues that this form of vernacular criticism arrives at a productive convergence with contemporary academic critical methodologies in surface and postcritical reading practices, on the one hand, and digital humanities, on the other. The data-oriented character of the Bechdel Test, which a text rigidly passes or fails, stands in sharp contrast to identification- or recognition-based evaluations of a text’s feminist orientation, particularly because the former does not prescribe the content, but merely the social form, of women’s agency. This essay connects the Bechdel Test and a lineage of feminist and early queer theory to current work on social network analysis within literary texts, and it argues that the Bechdel Test offers the beginnings of a measured approach to understanding agency within actor networks

Computational Stylistics in Poetry, Prose, and Drama

The contributions in this edited volume approach poetry, narrative, and drama from the perspective of Computational Stylistics. They exemplify methods of computational textual analysis and explore the possibility of computational generation of literary texts. The volume presents a range of computational and Natural Language Processing applications to literary studies, such as motif detection, network analysis, machine learning, and deep learning

Frontiers in Comparative Metrics IV, 16–17 September 2022, Tallinn, Estonia

Frontiers in Comparative Metrics IV, 16–17 September 2022, Tallinn, Estoni

Comparison of Style Features for the Authorship Verification of Literary Texts

The article compares character-level, word-level, and rhythm features for the authorship verification of literary texts of the 19th-21st centuries. Text corpora contains fragments of novels, each fragment has a size of about 50 000 characters. There are 40 fragments for each author. 20 authors who wrote in English, Russian, French, and 8 Spanish-language authors are considered.The authors of this paper use existing algorithms for calculation of low-level features, popular in the computer linguistics, and rhythm features, common for the literary texts. Low-level features include n-grams of words, frequencies of letters and punctuation marks, average word and sentence lengths, etc. Rhythm features are based on lexico-grammatical figures: anaphora, epiphora, symploce, aposiopesis, epanalepsis, anadiplosis, diacope, epizeuxis, chiasmus, polysyndeton, repetitive exclamatory and interrogative sentences. These features include the frequency of occurrence of particular rhythm figures per 100 sentences, the number of unique words in the aspects of rhythm, the percentage of nouns, adjectives, adverbs and verbs in the aspects of rhythm. Authorship verification is considered as a binary classification problem: whether the text belongs to a particular author or not. AdaBoost and a neural network with an LSTM layer are considered as classification algorithms. The experiments demonstrate the effectiveness of rhythm features in verification of particular authors, and superiority of feature types combinations over single feature types on average. The best value for precision, recall, and F-measure for the AdaBoost classifier exceeds 90% when all three types of features are combined