Digital Communication and Language

Últimos artículos

• Two Emojis of Difference: What Multilingual Affective Generation Benchmarks Actually Measure

  Fardeen Sadab, Adib Sakhawat · 25 de septiembre de 2026

  We audit a multilingual affective generation benchmark eight instruction-tuned LLMs producing emoji summaries for 17,100 Bangla, English and Hindi sentences, with 6,960 human judgements and find its headline conclusions to be artefacts of the measurement instrument rather than properties of the syst…

• Digital diglossia: Arabic between X and Facebook

  Fahad Al Hussen (King Saud University, Riyadh, Saudi Arabia), Mohammed Q. Shormani (Ibb University, Ibb, Yemen) · 24 de septiembre de 2026

  This study highlights the distribution of Standard Arabic (SA; H(igh) variety) and Colloquial Arabic (CA; L(ow) variety) across X and Facebook. 16754 public posts were collected via Python, with 10000 retained as the net dataset. Posts were classified into 7 discourse categories: *politics, technolo…

• Machine learning and digital pragmatics: Which word category influences emoji use most?

  Mohammed Q. Shormani, Yehia A. AlSohbani, Mohammed Q. Shormani · 25 de agosto de 2026

  This study examines the performance of the state-of-the-art MARBERT model in identifying the lexical/pragmatic category associated with emoji use on X within a digital pragmatics approach (DPA). A net corpus of 15856 Colloquial Arabic (CA) posts containing emojis was collected from X using Python. T…

• PERCEPT: A Corpus for POS Tagging and Analysis of Persian-English Code-Mixing

  Ghazal Kalhor, Zahra Jafari, Amirarsalan Shahbazi, Behnam Bahrak · 12 de agosto de 2026

  Social media has become a major venue for multilingual communication, where users frequently mix multiple languages within a single utterance. Although code-mixed corpora have been developed for several language pairs, Persian-English code-mixing remains relatively underexplored. Existing Persian re…

• Does Machine "know" interpersonal pragmatics? Evidence from MARBERT's learning of emoji pragmatics in Arabic digital discourse

  Mohammed Q. Shormani · 4 de agosto de 2026

  This study examines Transformer-based models' ability to learn emoji pragmatics in Arabic digital discourse (ADD), providing evidence from MARBERT's behavior with interpersonal pragmatic functions (IPFs). A corpus of 8,504 unique emoji-posts collected from Facebook via Python was used in the study. …

• False Friends in the Shell: Unveiling the Emoticon Semantic Confusion in Large Language Models

  Weipeng Jiang, Xiaoyu Zhang, Juan Zhai, Shiqing Ma, Chao Shen, Yang Liu · 6 de mayo de 2026

  Emoticons are widely used in digital communication to convey affective intent, yet their safety implications for Large Language Models (LLMs) remain largely unexplored. In this paper, we identify emoticon semantic confusion, a vulnerability where LLMs misinterpret ASCII-based emoticons to perform un…

• Machine learning and emoji prediction: How much accuracy can MARBERT achieve?

  Mohammed Q. Shormani, Ibrahim Abdulmalik Hassan Muneef Y. Alshawsh · 27 de abril de 2026

  This study investigates Machine Learning (ML) in the prediction of emojis in Arabic tweets employing the (state-of-the-art) MARBERT model. A corpus of 11379 CA tweets representing multiple Arabic colloquial dialects was collected from X.com via Python. A net dataset includes 8695 tweets, which were …

• Machine learning and digital pragmatics: Which word category influences emoji use most?

  Mohammed Q. Shormani, Ibrahim Abdulmalik Hassan Muneef Y. Alshawsh · 24 de abril de 2026

  This study investigates Machine Learning (ML) in the prediction of emojis in Arabic tweets employing the (state-of-the-art) MARBERT model. A corpus of 11379 CA tweets representing multiple Arabic colloquial dialects was collected from X.com via Python. A net dataset includes 8695 tweets, which were …

• EnTaCs: Analyzing the Relationship Between Sentiment and Language Choice in English-Tamil Code-Switching

  Paul Bontempo · 30 de marzo de 2026

  This paper investigates the relationship between utterance sentiment and language choice in English-Tamil code-switched text, using methods from machine learning and statistical modelling. We apply a fine-tuned XLM-RoBERTa model for token-level language identification on 35,650 romanized YouTube com…

• Reading Between the Lines: How Electronic Nonverbal Cues shape Emotion Decoding

  Taara Kumar, Kokil Jaidka · 24 de marzo de 2026

  As text-based computer-mediated communication (CMC) increasingly structures everyday interaction, a central question re-emerges with new urgency: How do users reconstruct nonverbal expression in environments where embodied cues are absent? This paper provides a systematic, theory-driven account of e…

• Causal Effects of Trigger Words in Social Media Discussions: A Large-Scale Case Study about UK Politics on Reddit

  Dimosthenis Antypas, Christian Arnold, Nedjma Ousidhoum, Carla Perez Almendros, Jose Camacho-Collados · 4 de marzo de 2026

  Political debates on social media often escalate quickly, leading to increased engagement as well as more emotional and polarised exchanges. Trigger points (Mau, Lux, and Westheuser 2023) represent moments when individuals feel that their understanding of what is fair, normal, or appropriate in soci…

• Early Multimodal Prediction of Cross-Lingual Meme Virality on Reddit: A Time-Window Analysis

  Sedat Dogan, Nina Dethlefs, Debarati Chakraborty · 24 de febrero de 2026

  Memes are a central part of online culture, yet their virality remains difficult to predict, especially in cross-lingual settings. We present a large-scale, time-series dataset of 46,578 Reddit memes collected from 25 meme-centric subreddits across eight language groups, with more than one million e…

• Stickers on Facebook: Multifunctionality and face-enhancing politeness in everyday social interaction

  Laura M. Porrino-Moscoso · 10 de febrero de 2026

  Stickers are multimodal resources widely used in everyday digital conversations. Despite their popularity, most studies have focused on emojis and emoticons. Therefore, this study analyzes, from a sociopragmatic perspective, the use of stickers in the comments from a corpus of Facebook posts contain…

• When Handwriting Goes Social: Creativity, Anonymity, and Communication in Graphonymous Online Spaces

  Aditya Kumar Purohit, Aditya Upadhyaya, Nicolas Ruiz, Alberto Monge Roffarello, Hendrik Heuer · 3 de febrero de 2026

  While most digital communication platforms rely on text, relatively little research has examined how users engage through handwriting and drawing in anonymous, collaborative environments. We introduce Graphonymous Interaction, a form of communication where users interact anonymously via handwriting …

• Persuasion in Online Conversations Is Associated with Alignment in Expressed Human Values

  Bhavesh Vuyyuru, Farnaz Jahanbakhsh · 21 de enero de 2026

  Online disagreements often fail to produce understanding, instead reinforcing existing positions or escalating conflict. Prior work on predictors of successful persuasion in online discourse has largely focused on surface features such as linguistic style or conversational structure, leaving open th…

• Small Symbols, Big Risks: Exploring Emoticon Semantic Confusion in Large Language Models

  Weipeng Jiang, Xiaoyu Zhang, Juan Zhai, Shiqing Ma, Chao Shen, Yang Liu · 14 de enero de 2026

  Emoticons are widely used in digital communication to convey affective intent, yet their safety implications for Large Language Models (LLMs) remain largely unexplored. In this paper, we identify emoticon semantic confusion, a vulnerability where LLMs misinterpret ASCII-based emoticons to perform un…

• Emoji Reactions on Telegram: Unreliable Indicators of Emotional Resonance

  Serena Tardelli, Lorenzo Alvisi, Lorenzo Cima, Stefano Cresci, Maurizio Tesconi · 22 de diciembre de 2025

  Emoji reactions are a frequently used feature of messaging platforms, yet their communicative role remains understudied. Prior work on emojis has focused predominantly on in-text usage, showing that emojis embedded in messages tend to amplify and mirror the author's affective tone. This evidence has…

• V-VAE: A Variational Auto Encoding Framework Towards Fine-Grained Control over Human-Like Chat

  Qi Lin, Weikai Xu, Lisi Chen, Bin Dai · 12 de diciembre de 2025

  With the continued proliferation of Large Language Model (LLM) based chatbots, there is a growing demand for generating responses that are not only linguistically fluent but also consistently aligned with persona-specific traits in conversations. However, existing role-play and persona-based chat ap…

• Social Perceptions of English Spelling Variation on Twitter: A Comparative Analysis of Human and LLM Responses

  Dong Nguyen, Laura Rosseel · 1 de diciembre de 2025

  Spelling variation (e.g. funnnn vs. fun) can influence the social perception of texts and their writers: we often have various associations with different forms of writing (is the text informal? does the writer seem young?). In this study, we focus on the social perception of spelling variation in o…