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MARBERT learns emoji pragmatics in Arabic digital discourse

By PulseAugur Editorial · [1 sources] ·

A new study published on arXiv explores how Transformer-based models, specifically MARBERT, can learn interpersonal pragmatics in Arabic digital discourse through the use of emojis. Researchers collected and annotated a dataset of over 8,500 emoji-posts from Facebook, labeling them for functions like politeness, respect, solidarity, empathy, and encouragement. The findings indicate that MARBERT achieved high accuracy in identifying these pragmatic functions, demonstrating its capability to understand beyond basic sentiment analysis, though it still struggles with highly implicit social meanings. AI

IMPACT Demonstrates advanced NLP capabilities in understanding nuanced social communication, potentially improving AI's ability to engage in culturally sensitive digital interactions.

RANK_REASON The item is a research paper detailing a study on machine learning models' capabilities. [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 →

MARBERT learns emoji pragmatics in Arabic digital discourse

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The item is a research paper detailing a study on machine learning models' capabilities. [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 (Ibb University) ·

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

    arXiv:2608.01174v1 Announce Type: new Abstract: 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 em…

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