Identification of sarcasm in texts for sentimental analysis

Rаhhimov , Khаsаnboy, Рахимов , Хасанбой, Rаximov , Xаsаnboy

Хорижий лингвистика ва лингводидактика · 2024-yil

Annotatsiya

Humanity has discovered various ways to express emotions. Depending on the context of speech, these emotions are sometimes accompanied by sarcasm, particularly when expressing intense feelings. Over the past few decades, social media platforms such as Facebook, Instagram, TikTok, Twitter, and YouTube have become popular tools for people to share such strong emotions and personal thoughts with wide audiences. Through techniques like sentiment analysis, this data can be valuable in various fields, including business, marketing, production, behavioral analysis, and public management during ecological or biological crises, as well as in times of war. Most current research treats sentiment and sarcasm classification as two separate tasks, approaching each as an independent text classification problem. In recent years, studies using deep learning algorithms have significantly improved the effectiveness of these independent classifiers. However, one of the main challenges these approaches face is their inability to accurately classify sarcastic statements as negative. Taking this into account, we argue that recognizing sarcasm enhances sentiment classification, and vice versa. In this work, we demonstrate that these two tasks are interrelated. This paper proposes a multi-task learning framework that leverages deep neural networks to model this interrelation, aiming to improve the overall effectiveness of sentiment analysis.

Maqola ma’lumotlari
MualliflarRаhhimov , Khаsаnboy, Рахимов , Хасанбой, Rаximov , Xаsаnboy
JurnalХорижий лингвистика ва лингводидактика
Nashr sanasi2024-10-25
Jild2
Son4/S
Betlar95-104
TilO‘zbek
DOI10.47689/2181-3701-vol2-iss4/s-pp95-104

DOI: 10.47689/2181-3701-vol2-iss4/s-pp95-104 · Maqolaning asl sahifasi

Kalit so‘zlar

sentiment analizi, ijtimoiy media platformalari, NLP, kinoya(sarcazm), deep learning algoritm, multi-task learning, polaritet, tokenizatsiya, анализ тональности, платформы социальных сетей, NLP, сарказм, алгоритмы глубокого обучения, обучение с несколькими задачами, полярность, токенизация, sentiment analysis, social media platforms, NLP, sarcasm, deep learning algorithm, multi-task learning, polarity, tokenization

Ilmiy soha

FilologiyaPedagogika

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