Natural Language Processing: Recent Advances and Applications

Dear Colleagues,

Natural Language Processing (NLP) has experienced remarkable growth over the past decade, transforming the way we engage with textual data across diverse knowledge domains. As NLP techniques become more accessible and robust, we witness their increasing application not only in traditional tasks such as sentiment analysis or information retrieval but also in areas that demand deeper sensitivity to historical nuance, linguistic variability, and rich contextual interpretation.

This Special Issue aims to bring together recent advances in NLP that push the boundaries of how we process, understand, and generate text in complex, often multilingual, and historically or culturally layered contexts. In particular, we are interested in computational models that address the challenges of representing meaning and modeling language understanding and acquisition. Studies that explore novel frameworks for knowledge representation—grounded in linguistic theory, cognitive modeling, or data-driven abstraction—are particularly welcome to be submitted to this Special Issue.

We encourage submissions that address text normalization, genre detection, stylistic variation, or the interpretation of symbolic and metaphorical language, as well as contributions that engage with computational approaches to semantic construction and the mechanisms by which humans and machines alike acquire linguistic competence. Furthermore, we welcome the submission of work that explores new ways to generate or analyze creative texts such as poetry or narrative or that focuses on the design of models capable of navigating ambiguity, figurative speech, and culturally situated meaning.

We also welcome studies that use explainable or interpretable models to uncover linguistic patterns in texts associated with social or political movements or that examine the evolution of language over time using large-scale corpora. Studies that highlight interdisciplinary collaborations between computational scientists and scholars in the humanities and cognitive sciences—particularly when they generate novel methodological insights—are strongly encouraged to be submitted to this Special Issue.

We invite the submission of original research articles, review papers, position pieces, and short communications focused on topics that include, but are not limited to, the following:

• Text processing methods tailored to historical, literary, or non-canonical corpora;
• Techniques for text normalization, error correction, or dialectal variation handling;
• Computational modeling of textual genres and stylistic markers;
• Narrative generation and automated storytelling based on domain-specific data;
• Semantic analysis and computational models of meaning construction;
• Computational approaches to language acquisition and grammatical generalization;
• NLP applications for large-scale document indexing and retrieval in archival contexts;
• Integration of NLP techniques into exploratory interfaces for cultural or linguistic collections;
• Applications of language models to enhance the interpretation of symbolic or creative texts;
• Visualization of linguistic structures in large text collections.

By emphasizing recent technical advances alongside thoughtful theoretical and interdisciplinary contributions, this Special Issue seeks to showcase how NLP can meaningfully advance our understanding of language, cognition, and cultural expression.

Prof. Dr. Hiram Calvo
Dr. Pablo Gervás
Guest Editors

Manuscript Submission Information

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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

• knowledge representation and meaning construction
• computational models of language and language acquisition
• language variation
• genre detection
• semantic modeling
• automated storytelling
• interpretable NLP
• cultural data modeling
• computational stylistics