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Digital diglossia: Arabic between X and Facebook
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arXiv Computation and Language
Sep 24
Digital diglossia: Arabic between X and Facebook
The study examines how Standard Arabic (SA) and Colloquial Arabic (CA) are distributed across X and Facebook by analyzing 10,000 public posts classified into seven discourse categories. Statistical tests reveal significant associations between discourse category and diglossic choice on both platforms, with platform also influencing diglossic choice. Logistic regression shows higher odds of SA use on X in certain domains, indicating that digital platforms reshape but do not erase diglossic boundaries.
arXiv Computation and Language
22h ago
AraEngage: Interpretable Linguistic Correlates of Engagement in Arabic Facebook News
arXiv:2611.07926v1 Announce Type: new Abstract: Engagement features developed for English are routinely applied to Arabic, but unvocalized Arabic changes what a lexical feature measures. We introduce...
arXiv Computation and Language
Aug 25
Machine learning and digital pragmatics: Which word category influences emoji use most?
arXiv:2608.21975v1 Announce Type: new Abstract: 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...
arXiv Computation and Language
Aug 25
A Comprehensive Analysis of Arabic Natural Language Processing Research: Trends, Topic Evolution, and Research Gaps -- A Bibliometric and Topic-Based Study
arXiv:2608.23421v1 Announce Type: new Abstract: Natural Language Processing (NLP) has grown rapidly over the past decade, driven by digital transformation in the Arab world, social media, and large l...
Hugging Face Trending Papers
Aug 24
A Comprehensive Analysis of Arabic Natural Language Processing Research: Trends, Topic Evolution, and Research Gaps -- A Bibliometric and Topic-Based Study
Arabic Natural Language Processing (NLP) has grown rapidly over the past decade, driven by digital transformation in the Arab world, social media, and large language models (LLMs). Despite this growth...
arXiv Computation and Language
Sep 24
The Illinois Social Attitudes Aggregate Corpus (ISAAC): An Open Tool and Reproducible Pipeline for Analyzing Social Group Discourse at Scale
The Illinois Social Attitudes Aggregate Corpus (ISAAC) is an open, modular corpus comprising over 527 million English‑language Reddit posts from 2007 to 2023, curated for relevance to six social group distinctions—race, sexuality, age, ability, body weight, and skin tone. A multi‑step, human‑audited filtering pipeline keeps irrelevant content below 10% overall and per group, while each post receives algorithmic annotations of user home region and a suite of validated semantic labels such as moralization, sentiment, emotion, and linguistic generalization. ISAAC’s publicly available, reproducible pipeline enables cross‑category comparisons, high‑precision tracking of long‑term temporal shifts, and spatial mapping of public opinion and policy outcomes, and can be extended to new platforms, languages, and social categories via both point‑and‑click and programmatic interfaces.