Телеграм канал «RESEARCH RESULT. THEORETICAL AND APPLIED LINGUISTICS»

🧬 2025 Year in Review: Channel Highlights & Journal Issue No. 4 Dear colleagues and friends, 2025 has been a dynamic year for our academic community. We've explored new tools, discussed groundbreaking research, and engaged with the evolving landscape of linguistics. Let's revisit the key highlights from our channel and introduce the latest issue of our journal. 🔥 Top 5 Highlights from the RR_Linguistics Channel in 2025 🤖 AI as a Research Partner We delved into practical guides for integrating AI (like the Perplexity handbook) and Kaggle micro-courses for linguists. The key takeaway: AI is not a replacement for the scholar, but a powerful tool for automating routine tasks and analyzing data, freeing you to focus on deep, conceptual work. 🛠️ The Digital Linguist's Toolkit We spotlighted essential tools for modern analysis: BibExcel for bibliometrics and citation network analysis. Scopus AI for intelligent literature discovery and mapping. The future of quality assurance was debated in our coverage of Peer Review Week 2025. 👶 Groundbreaking Research A major focus was the landmark PNASstudy revealing how infants use vowel information to categorize objects and build their first lexicon. This work challenges fundamental assumptions about early language acquisition. 📈 Skills for Modern Science A recurring theme was digital and meta-scientific literacy. We emphasized the growing need for skills in data processing, visualization, and the critical evaluation of scientific literature in the digital age. 📖 Presenting "Linguistics" Journal, Issue No. 4, 2025 Alongside our channel activity, our peer-reviewed journal has continued its regular publication. The fresh fourth issue of 2025 features articles that resonate with many of the topics we've discussed: Theoretical Linguistics & Grammar: In-depth analysis of language systems and structures. Cognitive & Experimental Research: Work at the intersection of linguistics and psychology. Socio- & Pragmalinguistics: Study of language in its social context. Digital Methods & Corpus Linguistics: Application of new computational tools for language data analysis. This issue reflects the broad spectrum of contemporary scholarly inquiry in the science of language. 🔗 Dive Deeper: The fourth journal issue for 2025: https://rrlinguistics.ru/media/linguistics/2025/4/%D0%9B%D0%B8%D0%BD%D0%B3%D0%B2%D0%B8%D1%81%D1%82%D0%B8%D0%BA%D0%B0_114_vIORCC0.pdf Thank you for being part of our community this year. We look forward to continuing these open discussions with you on the pages of Research Result.Theoretical and Applied Linguistics in 2026.

🔧 Tool Spotlight: BibExcel for Bibliometric Analysis Wondering how to dive into the formal analysis of academic literature, citation networks, or author collaborations? The classic, free tool BibExcel is a powerful option designed specifically for this task. What is BibExcel? Created by Olle Persson, BibExcel is a toolbox that helps you analyze bibliographic data (like records from Web of Science) or any similarly formatted text data. Its core function is to process raw data and prepare it for import into Excel or other tabular programs for further analysis and visualization. What Can Linguists Do With It? While used across sciences, it's highly relevant for meta-research in linguistics. You can use it for: 📊 Citation Analysis & Bibliometrics: Study the impact and connections within a body of linguistic literature. 👥 Co-authorship & Collaboration Analysis: Map networks of researchers in sub-fields. 🔗 Co-citation Analysis & Bibliographic Coupling: Identify related papers, seminal works, and research fronts. 🗺️ Preparing Data for Mapping: Generate files for network visualization tools like Pajek. Key Practical Details Cost & Use: It's freeware for academic, non-profit use. Format: It primarily works with ISI/Web of Science records but can convert some other formats. Process: It's not a single-click tool. You use different modules to clean, count, and structure data before final analysis in a spreadsheet or visualization software. Getting Started & Learning Download: The latest version and help files are available from the official page. Learn: The page provides sample data and 16 step-by-step exercises (using co-citation studies) which are the best way to learn. Explore: Check the linked "Festschrift" chapter and audiovisual courses for deeper understanding. If you use it in your research, you have to cite the recommended paper by Persson et al. 🔗 Resources: Download & Exercises: BibExcel Homepage Recommended Citation: Persson, O., Danell, R., & Wiborg Schneider, J. (2009). How to use Bibexcel for various types of bibliometric analysis.

7. Linguistics of Crisis Communication: Discourse Analysis of Emergencies. Comparative analysis of official statements, media, and social media during crises (pandemics, natural disasters). Identifying effective and destructive language patterns to create crisis communication protocols. 8. Ecolinguistics: Discourse of Sustainable Development in Corporate Reports and Media. Critical analysis of language used by large corporations ("greenwashing") and media when covering ecology and sustainable development. Developing linguistic criteria for assessing the credibility of "green" claims. We invite submissions from scholars worldwide! Journal Website: http://rrlinguistics.ru Submit your manuscript and contribute to cutting-edge linguistic research.

Dear colleagues and friends! We receive hundreds of submissions every week, and we really regret to reject high quality papers which are not within the journal’s scope. We have decided to highlight the topics the journal is currently interested in. Research Result. Theoretical and Applied Linguistics: Scope of the Journal What topics can you publish on? Our journal welcomes high-quality research at the intersection of linguistics and modern technological and social challenges. Below is a representative, though not exhaustive, list of our current key thematic priorities. 1. Corpus Linguistics (outside the context of foreign language teaching). 2. Applied Aspects of Academic Writing. 3. Linguistic Behavior in Machine-Generated Environments. 4. Linguistic Aspects of AI Research (Large Language Models - LLMs) Psycholinguistic Testing of LLMs: Adapting methodologies from psycholinguistics (e.g., reaction time measurement) to assess the linguistic competence of AI. For instance, testing a model's sensitivity to grammatical anomalies or semantic mismatches. Optimization and Ethics of LLMs for Low-Resource Languages: Analyzing and mitigating biases in LLMs (e.g., GPT, Llama) when working with Russian, Tatar, Bashkir, other languages of Russia, and world languages. Developing methods for efficient and energy-frugal fine-tuning on limited text corpora. Linguistic Support for AI in Robotics: Investigating how linguistic principles (speech acts, implicatures, discourse management) can enhance human-robot interaction. For example, how a robot should verbally respond to non-standard commands or its own errors. 5. Methodology: Mathematical, Statistical, and Computational Methods for Analyzing Linguistic and Social Phenomena. Cross-Lingual Disinformation and Propaganda Detection: Creating systems that analyze not just translation, but also linguistic markers of manipulation (logical fallacies, emotional loading, framing) during the cross-lingual spread of fake news. Linguistic Expertise of Disinformation in Digital Media: Developing a comprehensive model for identifying manipulative language strategies (framing, use of metaphors, narrative constructions) in news texts and social media. Creating an annotated corpus for algorithm training. Linguistically-Motivated Data Augmentation for Model Training: Using knowledge of word formation, synonymy, and syntactic transformations to generate high-quality additional training data, beyond simple random word replacement. Linguistic Markers of Mental Health in User-Generated Texts: Analyzing written texts (social media posts, diaries) using NLP to identify linguistic patterns correlating with depression, anxiety, burnout. Aim: creating tools for early screening. Linguistic Design of User Interfaces (UX Writing) and Chatbots for Critical Services: Researching how wording, tone, and text structure in interfaces for government services, banking, or healthcare affect accessibility, trust, and user efficiency. Discourse Analysis of Healthcare Communication in the Digital Age: Studying communicative failures in online consultations (telemedicine). Developing recommendations and scripts for doctors to improve patient adherence and satisfaction. 6. Machine Translation vs. Human Translation Interpretability and Explainability (XAI) of Neural Translation "Black Boxes": Developing methods to "look inside" transformers and LLMs to understand how they represent linguistic knowledge (syntax, semantics, discourse). Controlling Style and Register in Machine Translation via Linguistic Prompts: Researching how subtle linguistic descriptors in prompts ("translate in a scientific register," "make the text more formal using passive voices") affect translation quality and adequacy. Multimodal Machine Translation for Social Media: Developing translation models that account for visual context (images, memes, infographics) to resolve lexical ambiguity and convey cultural references.

Generation and Translation for Immersive Environments (VR/AR): Creating systems for translating and adapting textual and speech components in virtual and augmented reality, considering spatial context. Machine Translation for Low-Resource and Endangered Languages: Developing methods that do not require large parallel corpora (zero-shot, few-shot learning, active learning) to preserve and support linguistic diversity. Cognitive-Ergonomic Assessment of Translation Quality: Investigating how machine translation affects user cognitive load (speed of comprehension, information retention, decision-making). Using eye-tracking and EEG. Automated Content Adaptation for Video Game Localization: Developing algorithms for translating and culturally adapting not only dialogue but also in-game content (item names, lore), considering interactivity and non-linear narrative. Pre-Translation Analysis and Post-Editing Systems: Creating intelligent assistants that automatically determine text complexity, suggest term translation options, and help professional translators work more efficiently with MT output. 7. Linguistics of Crisis Communication: Discourse Analysis of Emergencies. Comparative analysis of official statements, media, and social media during crises (pandemics, natural disasters). Identifying effective and destructive language patterns to create crisis communication protocols. 8. Ecolinguistics: Discourse of Sustainable Development in Corporate Reports and Media. Critical analysis of language used by large corporations ("greenwashing") and media when covering ecology and sustainable development. Developing linguistic criteria for assessing the credibility of "green" claims. We invite submissions from scholars worldwide! Journal Website: http://rrlinguistics.ru Submit your manuscript and contribute to cutting-edge linguistic research.