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<p>Sentiment Analysis (SA) is metaphor for&#xa0;opinion mining&#xa0;and being leveraged in emotion detection. SA of text is being performed by&#xa0;Natural Language Processing (NLP) using&#xa0;computational and linguistic resources in amalgamation with biometric&#xa0;to systematic identification by extracting affective states and subjective information<b>.</b> In order to analyze the sentiments; data is gathered through user&#xa0;generated online content such as review forms, questionnaires, survey responses, social media posts and healthcare records from medical applications. With the help of deep-learning based language models, complex domains like news texts where authors typically express their opinion/sentiment less clearly; analyzing more precisely. Urdu language is credited as the 21st most spoken language in the world. Among its South Asian users, Urdu written in Roman script (also known as Roman Urdu), has become very popular. Roman Urdu stands as the 3rd most frequently used language following English and mandarin Chinese. We aim to conduct a comprehensive survey on wide range techniques applicable to user generated content for various languages, particularly for Urdu and Roman Urdu. This survey will highlight and pave the path towards high performance, upgraded, corrected and speedy approaches of SA.</p>

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A comparative study of sentiment analysis in urdu and roman urdu: the neglected realms

  • 期刊论文

  • 发表日期：

    2025年7月29日

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  • Sadia Tariq,
  • Toqir A. Rana,
  • Fatima Shahzadi

摘要

Sentiment Analysis (SA) is metaphor for opinion mining and being leveraged in emotion detection. SA of text is being performed by Natural Language Processing (NLP) using computational and linguistic resources in amalgamation with biometric to systematic identification by extracting affective states and subjective information. In order to analyze the sentiments; data is gathered through user generated online content such as review forms, questionnaires, survey responses, social media posts and healthcare records from medical applications. With the help of deep-learning based language models, complex domains like news texts where authors typically express their opinion/sentiment less clearly; analyzing more precisely. Urdu language is credited as the 21st most spoken language in the world. Among its South Asian users, Urdu written in Roman script (also known as Roman Urdu), has become very popular. Roman Urdu stands as the 3rd most frequently used language following English and mandarin Chinese. We aim to conduct a comprehensive survey on wide range techniques applicable to user generated content for various languages, particularly for Urdu and Roman Urdu. This survey will highlight and pave the path towards high performance, upgraded, corrected and speedy approaches of SA.