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Study finds verbs most influential for emoji use on X

By PulseAugur Editorial · [1 sources] ·

A new study published on arXiv explores the influence of different word categories on emoji usage within the Arabic language on the X platform. Researchers utilized the MARBERT model and Python to analyze a corpus of over 15,000 posts, categorizing words into nouns, verbs, adjectives, adverbs, questions, and exclamations. While nouns were the most frequent, verbs demonstrated the strongest statistical association with emoji use, suggesting a hybrid approach combining machine learning, linguistic features, and pragmatic communication is key to understanding this digital interaction. AI

IMPACT Provides insights into how language models can analyze nuanced linguistic features in social media communication.

RANK_REASON Academic paper on linguistic analysis using ML. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CL →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Study finds verbs most influential for emoji use on X

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Academic paper on linguistic analysis using ML. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.CL TIER_1 English(EN) · Mohammed Q. Shormani, Yehia A. AlSohbani, Mohammed Q. Shormani ·

    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 within a digital pragmatics approach (DPA). A net corpus of 15856 Colloquial Arab…

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