Search Results (14)

This study proposes an artificial intelligence (AI)-powered multimodal system designed to enhance the appreciation of traditional poetry, using Japanese haiku as the primary application domain. At the core of the system is an intelligent data analysis pipeline that extracts key emotional features from poetic texts. A fine-tuned Japanese BERT model is employed to compute three affective indices—valence, energy, and dynamism—which form a quantitative emotional representation of each haiku. These features guide a generative AI workflow: ChatGPT constructs structured image prompts based on the extracted affective cues and contextual information, and these prompts are used by DALL·E to synthesize stylistically consistent watercolor illustrations. Simultaneously, background music is automatically selected from an open-source collection by matching each poem’s affective vector with that of instrumental tracks, producing a coherent multimodal (text, image, sound) experience. A series of validation experiments demonstrated the reliability and stability of the extracted emotional features, as well as their effectiveness in supporting consistent cross-modal alignment. These results indicate that poetic emotion can be represented within a low-dimensional affective space and used as a bridge across linguistic and artistic modalities. The proposed framework illustrates a novel integration of affective computing and natural language processing (NLP) within cultural computing. Because the underlying emotional representation is linguistically agnostic, the system holds strong potential for cross-cultural extensions, including applications to Chinese classical poetry and other forms of traditional literature. Full article

This entry presents a comprehensive overview of the computational study of Old English that surveys the evolution from early digital corpora to recent artificial intelligence applications. Six interconnected domains are examined: textual resources (including the Helsinki Corpus, the Dictionary of Old English Corpus, and the York-Toronto-Helsinki Parsed Corpus), lexicographical resources (analysing approaches from Bosworth–Toller to the Dictionary of Old English), corpus lemmatisation (covering both prose and poetic texts), treebanks (particularly Universal Dependencies frameworks), and artificial intelligence applications. The paper shows that computational methodologies have transformed Old English studies because they facilitate large-scale analyses of morphology, syntax, and semantics previously impossible through traditional philological methods. Recent innovations are highlighted, including the development of lexical databases like Nerthusv5, dependency parsing methods, and the application of transformer models and NLP libraries to historical language processing. In spite of these remarkable advances, problems persist, including limited corpus size, orthographic inconsistency, and methodological difficulties in applying modern computational techniques to historical languages. The conclusion is reached that the future of computational Old English studies lies in the integration of AI capabilities with traditional philological expertise, an approach that enhances traditional scholarship and opens new avenues for understanding Anglo-Saxon language and culture. Full article

In the era of generative artificial intelligence, writing has evolved into a programmable practice capable of generating sustainable narratives and preserving cultural heritage through poetic prompts. This study proposes “Writing Is Coding ” as a paradigm for sustainability education, exploring how students engage with AI-mediated multimodal creation to address environmental challenges. Using grounded theory methodology with 57 twelfth-grade students from technology-integrated high schools, we analyzed their experiences creating environmental stories and digital cultural artifacts using MidJourney, Kling, and Sora. Data collection involved classroom observations, semi-structured interviews, and reflective journals, analyzed through systematic coding procedures (κ = 0.82). Five central themes emerged: writing as algorithmic design for sustainability (89.5%), emotional scaffolding for environmental awareness (78.9%), aesthetics of imperfection in cultural preservation (71.9%), collaborative dynamics in sustainable creativity (84.2%), and pedagogical value of prompt literacy (91.2%). Findings indicate that AI deepens environmental consciousness and reframes writing as a computational process for addressing global issues. This research contributes a theoretical framework integrating expressive writing with algorithmic thinking in AI-assisted sustainability education, aligned with SDGs 4, 11, and 13. Full article

Existing approaches to the automatic annotation of classical Chinese poetry often fail to generate precise source citations and depend heavily on manual segmentation, limiting their scalability and accuracy. To address these shortcomings, we propose a novel paradigm that integrates dictionary retrieval with retrieval-augmented large language model enhancements for automatic poetic annotation. Our method leverages the contextual understanding capabilities of large models to dynamically select appropriate lexical senses and employs an automated segmentation technique to minimize reliance on manual splitting. For poetic segments absent from standard dictionaries, the system retrieves pertinent information from a domain-specific knowledge base and generates definitions grounded in this auxiliary data, thereby substantially improving both annotation accuracy and coverage. The experimental results demonstrate that our approach outperforms general-purpose large language models and pre-trained classical Chinese language models on automatic annotation tasks; notably, it achieves a micro-averaged accuracy of 94.33% on key semantic segments. By delivering more precise and comprehensive annotations, this framework advances the computational analysis of classical Chinese poetry and offers significant potential for intelligent teaching applications and digital humanities research. Full article

In this article, we focus on the association of sound and sense harmony in the collection of sonnets written by Shakespeare in the XVI° beginning of the XVII° century and propose a new four-dimensional representation to visualize them by means of the system called SPARSAR. To compute the degree of harmony and disharmony, we automatically extracted the sound grids of all the sonnets and combined them with the semantics and polarity expressed by their contents. We explain in detail the algorithm and show the representation of the whole collection of 154 sonnets and comment on them extensively. In a second experiment, we use data from the manual annotation of the sonnets for satire detection using the Appraisal Theory Framework, to gauge the system’s accuracy in matching these data with the output of the automatic algorithm for sound–sense harmony. The results obtained with a 94.6% accuracy confirm the obvious fact that the poet has to account for both sound and meaning in the choice of words. Full article

Aligned with global Sustainable Development Goals (SDGs) and multidisciplinary approaches integrating AI with sustainability, this research introduces an innovative AI framework for analyzing Modern French Poetry. It applies feature extraction techniques (TF-IDF and Doc2Vec) and machine learning algorithms (especially SVM) to create a model that objectively classifies poems by their stylistic and thematic attributes, transcending traditional subjective analyses. This work demonstrates AI’s potential in literary analysis and cultural exchange, highlighting the model’s capacity to facilitate cross-cultural understanding and enhance poetry education. The efficiency of the AI model, compared to traditional methods, shows promise in optimizing resources and reducing the environmental impact of education. Future research will refine the model’s technical aspects, ensuring effectiveness, equity, and personalization in education. Expanding the model’s scope to various poetic styles and genres will enhance its accuracy and generalizability. Additionally, efforts will focus on an equitable AI tool implementation for quality education access. This research offers insights into AI’s role in advancing poetry education and contributing to sustainability goals. By overcoming the outlined limitations and integrating the model into educational platforms, it sets a path for impactful developments in computational poetry and educational technology. Full article

Poetic devices implicitly work towards inducing the reader to associate intended and expressed meaning to the sounds of the poem. In turn, sounds may be organized a priori into categories and assigned presumed meaning as suggested by traditional literary studies. To compute the degree of harmony and disharmony, I have automatically extracted the sound grids of all the sonnets by William Shakespeare and have combined them with the themes expressed by their contents. In a first experiment, sounds have been associated with lexically and semantically based sentiment analysis, obtaining an 80% of agreement. In a second experiment, sentiment analysis has been substituted by Appraisal Theory, thus obtaining a more fine-grained interpretation that combines dis-harmony with irony. The computation for Francis Webb is based on his most popular 100 poems and combines automatic semantically and lexically based sentiment analysis with sound grids. The results produce visual maps that clearly separate poems into three clusters: negative harmony, positive harmony and disharmony, where the latter instantiates the need by the poet to encompass the opposites in a desperate attempt to reconcile them. Shakespeare and Webb have been chosen to prove the applicability of the method proposed in general contexts of poetry, exhibiting the widest possible gap at all linguistic and poetic levels. Full article

The paper focuses on the structure of an advertising image for a 2010s computer company in the neo-capitalist Moscow, Russia. The analysis looks back to the pioneering studies of advertising as a commercial “applied art” by Sergei Eisenstein, Leo Spitzer and Roland Barthes. The picture’s plot and composition are shown to be a consistent and sophisticated near-artistic design that uses textual puns, poetic topoi and visual stereotypes (in particular, sex appeal) for the promotion of the advertised merchandise (a smartphone). The psychological naturalization of the design is clarified with references to the insights of Sigmund Freud, Heinz Kohut and Gerard Genette into the dynamics of narcissism. In a widening circle, the contextualization of the design involves: the literary topos of using birds in love poetry (made famous by its treatment in the lyrics of the Roman poet Catullus) and in painterly variations on the theme; the narcissist discourse of a modern Russian poet (Eduard Limonov); and the grand pictorial tradition of portraying a nude (Venus) before the mirror (relevant classical canvases are considered briefly). Full article

In this paper, we compute the affective-aesthetic potential (AAP) of literary texts by using a simple sentiment analysis tool called SentiArt. In contrast to other established tools, SentiArt is based on publicly available vector space models (VSMs) and requires no emotional dictionary, thus making it applicable in any language for which VSMs have been made available (>150 so far) and avoiding issues of low coverage. In a first study, the AAP values of all words of a widely used lexical databank for German were computed and the VSM’s ability in representing concrete and more abstract semantic concepts was demonstrated. In a second study, SentiArt was used to predict ~2800 human word valence ratings and shown to have a high predictive accuracy (R² > 0.5, p < 0.0001). A third study tested the validity of SentiArt in predicting emotional states over (narrative) time using human liking ratings from reading a story. Again, the predictive accuracy was highly significant: R²_adj = 0.46, p < 0.0001, establishing the SentiArt tool as a promising candidate for lexical sentiment analyses at both the micro- and macrolevels, i.e., short and long literary materials. Possibilities and limitations of lexical VSM-based sentiment analyses of diverse complex literary texts are discussed in the light of these results. Full article

Choice poetics is a formalist framework that seeks to concretely describe the impacts choices have on player experiences within narrative games. Developed in part to support algorithmic generation of narrative choices, the theory includes a detailed analytical framework for understanding the impressions choice structures make by analyzing the relationships among options, outcomes, and player goals. The theory also emphasizes the need to account for players’ various modes of engagement, which vary both during play and between players. In this work, we illustrate the non-computational application of choice poetics to the analysis of two different games to further develop the theory and make it more accessible to others. We focus first on using choice poetics to examine the central repeated choice in “Undertale,” and show how it can be used to contrast two different player types that will approach a choice differently. Finally, we give an example of fine-grained analysis using a choice from the game “Papers, Please,” which breaks down options and their outcomes to illustrate exactly how the choice pushes players towards complicity via the introduction of uncertainty. Through all of these examples, we hope to show the usefulness of choice poetics as a framework for understanding narrative choices, and to demonstrate concretely how one could productively apply it to choices “in the wild.” Full article

The illustration of the “knowledge engine” included in early editions of Gulliver’s Travels is an engraving of a sketch from the notebook of Lemuel Gulliver. In other words, it is a purely fictional object. Yet, Swift's fictional invention and its graphic representations have become part of the documented historical lineage of computing machines. Furthermore, one of Swift’s purposes for inventing the “knowledge engine” was to satirize the scientific and technical cultures that now claim it as part of their history. As one piece of the elaborate discursive and material code of Gulliver’s Travels, “the knowledge engine,” its sources, and its reception offer some unique insights into the relationships that exist amongst factual and fictional narratives, scientific and humanistic discourse, words and images, and print and digital technologies. Although numerous scientific and philosophical texts have been cited as possible sources informing Swift’s satirical invention, this article considers a lesser known one, John Peter’s 1677 pamphlet Artificial Versifying, or the Schoolboy’s Recreation, which is itself a print-based textual machine for generating lines of Latin hexameter verse. Full article

Introduction to Special Issue "Poetics of Computation". This editorial is intended to serve as the introductory text to the entire issue. It attempts to tie several of the featured articles together thematically and critically together, while illustrating several common arguments that continue to inform studies in language, coding and the literary arts. Full article

Digital media and culture scholars routinely distinguish code from any common cultural understanding of media in order to underscore its wholly unique function as an epistemological tool. Where media emphasizes a hermeneutical relationship to knowledge as a mode of interpretation based on its graphic or symbolic representation, the idea of code in many ways invokes a far more complex and dynamic sense of how we determine meaning using symbols or signs in language in terms of producing actual programmable events. In the digital universe, computation, in terms of pre-coded rules, patterns and procedures, continues to showcase all objects and events, along with various corresponding behaviours or viabilities. This paper looks first at a range of contemporary philosophers, like Don Ihde, Katherine Hayles, David Berry and Bruno Latour, in order to build a theoretical foundation for understanding some of the changes in epistemology brought by digital technology and computational reason. Philosophies of computation, I argue, inevitably strive to outline a post-human culture and way of thinking about the world. Although the theoretical weaving of coding with human life follows in part from many earlier modern philosophical discussions on the role language plays in our thinking and sense of selfhood, we can see in computation a very specific reconceptualization of reasoning itself, producing, in turn, a host of new intellectual conflicts concerning human agency and our cognitive faculties. The paper then moves to explore two cultural examples of these conflicts, looking first at the practice of “live coding,” a unique, performative event where programmers demonstrate coding before a live audience. Whether on a physical stage in front of an actual audience or simply on screen as a live telecast, such performances combine with coding the distinct habits of gesture and voice in an improvised narrative. One single such show by live coder Sean Colombo is presented here in an exemplary reading of this relatively new media genre. A second, equally significant exploration of similar social and cultural conflicts associated with computation’s expansion into everyday living can be seen in the work of the digital literary artist, Ian Hatcher. Ian Hatcher’s consistently disturbing video enhanced performances evoke both the structure and overall ambience of a live coding event where he enacts the role of the coder/performer in a process of perpetual conflict with the text appearing on screen. While for many, the live coder can be heralded as a kind of exemplary humanist figure in computation, as these performances show, the more material, writerly aspects of coding must inevitably succumb to the cultural logic of the code’s literal execution to produce a distinctly post-humanist approach to writing and art. Full article

‘Reconfiguration: Symbolic Image and Language Art’ proposes an analytic and theoretical framework for computational aesthetic practices in terms of ‘reconfiguration’ and its derivatives, ‘reconfigurationism’ and ‘reconfigurationist’. Digitization of the media of aesthetic practices has rendered these practices subject to software architectures derived from computational applications that, for the most part, have had little regard for aesthetics as such. The ‘images’ of contemporary aesthetic practices are often ‘symbolic images’ in the terms of the essay. They are co-produced by networked computation and digitized—symbolized—representations of media, all within new formations of (‘Big’) software architectures that are, typically, beyond the artists’ generative, poetic control. Aesthetic practice is configured by software and digitalization. To bring art and aesthetics back into a generative relation with this potentially constrictive not to say totalizing situation, artists must reconfigure. This is an intervention that computation traditionally and productively allows, even in the era of Big Software. Reconfigurationism is demonstrated, specifically, in the field of language art and is also proposed as a poetics, characteristic of a wide range of contemporary aesthetic practice in all media where computation is at play. ‘Reconfiguration’ and ‘reconfigurationism’ distinguishes itself from theories of a ‘New Aesthetic’ and pretends a more insightful and critically generative analysis. The essay’s ‘symbolic image’ bears a relation to Vilém Flusser’s ‘technical image’ but has a clearer relation both to language and to computation, since Flusser’s term is overweening with regard to (the end of the history of) language and overdetermined by its links to apparatus as opposed to the generalized abstractions of computation. Full article