arXiv cs.CL· Mohammed Q. Shormani (Ibb University, Ibb, Yemen), Lamia Alhassoun (Arab Open University, Riyadh, Saudi Arabia), Yehia A. AlSohbani (Arab Open University, Riyadh, Saudi Arabia)·· 2 天前AI 评分18
MARBERT 研究：阿拉伯语 X 帖子中哪类词最影响 emoji 使用
Machine learning and digital pragmatics: Which word category influences emoji use most?
AI 导读
研究用 MARBERT 在 15856 条含 emoji 的阿拉伯语口语 X 帖子中识别与 emoji 使用相关的词类，发现名词在语料中频率最高（M = 0.675），但动词对 emoji 使用影响最强（β = 0.821，p = .001）。
正文 · 原文
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 within a digital pragmatics approach (DPA). A net corpus of 15856 Colloquial Arabic (CA) posts containing emojis was collected from X using Python. The texts were tokenized and normalized into 4 lexical categories, namely noun_norm, verb_norm, adj_norm, and adverb_norm, and 2 pragmatic/structural categories, question_norm and exclamation_norm. MARBERT was finetuned and optimized to identify which category scores standard metrics more, hence associated with emoji use, while binary logistic regression was used to examine which category is statistically associated with emoji occurrence. Findings unveil that nouns dominate the corpus in normalized frequency (M = 0.675, SD = 0.161), followed by verbs (M = 0.083, SD = 0.100). However, verbs have the strongest influence of emoji use indicated by verb density (\b{eta} = 0.821, p = .001, 95% CI [0.332, 1.309]). Findings further show that MARBERT performs comparatively well for verbs (precision = .74, recall = .99, F1 = .85) and nouns (precision = .88, recall = .44, F1 = .59), and substantially weaker for the less frequent categories. The study concludes that in digital pragmatics of CA on X, emoji use association with lexical/pragmatic category can be explained by a hybrid approach of computational, statistical, and pragmatic methods, reflecting the interaction among machine learning, linguistic/lexical features, contextual representation, and digital communication.
| Comments: | 18 pages, 3 tables |
| Subjects: | Computation and Language (cs.CL) |
| ACM classes: | F.2.2; I.2.7 |
| Cite as: | arXiv:2608.21975 [cs.CL] |
| (or arXiv:2608.21975v3 [cs.CL] for this version) | |
| https://doi.org/10.48550/arXiv.2608.21975 arXiv-issued DOI via DataCite |
Submission history
From: Mohammed Q. Shormani Mr [view email]
[v1]
Sat, 22 Aug 2026 14:23:38 UTC (590 KB)
[v2]
Sat, 19 Sep 2026 16:13:11 UTC (590 KB)
[v3]
Mon, 26 Oct 2026 20:54:10 UTC (591 KB)
来源：arXiv cs.CL · arxiv.org