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MARBERT model enhances Arabic tweet sentiment analysis for STC

By PulseAugur Editorial · [2 sources] ·

Researchers have developed a new model called MARBERT, based on the BERT architecture, for sentiment and spam detection specifically for Arabic tweets. The model was trained on a dataset of over 24,000 Arabic tweets related to Saudi Telecom Company (STC) to analyze customer sentiment and improve service. The study demonstrated promising accuracy compared to existing techniques. AI

IMPACT This research could improve customer service for Arabic-speaking users by enabling more accurate sentiment analysis of social media feedback.

RANK_REASON The cluster contains an academic paper detailing a new model and its application. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

MARBERT model enhances Arabic tweet sentiment analysis for STC

COVERAGE [2]

  1. arXiv cs.CL TIER_1 English(EN) · Abrar Alotaibi, Atta-ur Rahman, Raheel Alhaza, Wala Alkhalifa, Narjes Alhajjaj, Atheer Alharthi, Dhai Abushoumi, Maryam Alqahtani, Dania Alkhulaifi ·

    Spam and Sentiment Detection in Arabic Tweets Using MARBERT Model

    arXiv:2606.25495v1 Announce Type: new Abstract: Saudi Telecom Company (STC) is among the most popular companies in Saudi Arabia, with many customers. Yet, there is still a big room for improvement in users' satisfaction. Social media is the most robust platform to gauge users' sa…

  2. arXiv cs.AI TIER_1 English(EN) · Dania Alkhulaifi ·

    Spam and Sentiment Detection in Arabic Tweets Using MARBERT Model

    Saudi Telecom Company (STC) is among the most popular companies in Saudi Arabia, with many customers. Yet, there is still a big room for improvement in users' satisfaction. Social media is the most robust platform to gauge users' satisfaction and determine their sentiments and cr…

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