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42 results for “Sentiment Classification”
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Research ArticleOpen accessIn the keywordsSentiment Analysis: Comparative Study between GSVM and KNNHany Mohamed, Ayman Atia, Mostafa-Sami M. MostafaSentiment classification aims detecting general opinion of users in social media towards business products or daily life events. The classification tells whether sentiment is positive or negative. Techniques of sentiment classification are categorized into lexical analysis and machine learning techniques. In this paper, we propose a comparative study between SVM applied genetics (GSVM) against KNN algorithm in terms of speed … …American Journal of Applied Sciences, Vol. 15, Issue 6 · 1 Aug 2018 · 8,359 accessesView PDFCite
Research ArticleOpen accessIn the keywordsHybrid Deep Learning Models for Text Classification: Performance Evaluation of TriDistilBERT and BiGRU ArchitecturesAmira Samy TalaatText can be a valuable source of information, but its unstructured nature makes analysis challenging and time-consuming. Machine Learning (ML) algorithms can efficiently analyze and structure text, enabling organizations to automate processes and uncover insights that support better decision-making. This study focuses on applying ML to a classification problem using two datasets. Four deep learning models are introduced, combining Bi … …Journal of Computer Science, Vol. 21, Issue 9 · 10 Oct 2025 · 2,792 accessesView PDFCite
Review ArticleOpen accessIn the keywordsA Review on Challenging Issues in Arabic Sentiment AnalysisAli Hamdi, Khaled Shaban, Anazida ZainalUnderstanding what people think about an idea or how they evaluate a product, a service or a policy is important for individuals, companies and governments. Sentiment analysis is the process of automatically identifying opinions expressed in text on certain subjects. The accuracy of sentiment analysis has a direct effect on decision making in both business and government. Working with the … …Journal of Computer Science, Vol. 12, Issue 9 · 11 Dec 2016 · 8,422 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Transformer Based Model to Detect Environmental Related Distress on Online Social MediaUtkarsh Sharma, Prateek Pandey, Shishir KumarOnline social media has been recently employed as the source of data for the detection of traffic-related activities and to control the flow of traffic in smart cities all over the world. Till now an ample amount of research work has been done in identification of traffic-related incidents with the help of online social media platforms (mostly Twitter). Along with … …Journal of Computer Science, Vol. 22, Issue 11 · 9 Oct 2026 · 462 accessesView PDFCite
Research ArticleOpen accessIn the abstractDeep Learning Analysis of Drug Reviews: Identifying Patient Conditions, Predicting Drug Ratings, and Sentiment AnalysisRafat Hammad, Mohammad Ashraf Ottom, Ayah Bani BakerUnderstanding patients' experiences with medications is essential for improving drug effectiveness, detecting potential side effects, and enhancing overall patient satisfaction. This research investigates applying machine learning to patient drug reviews across three main tasks: Identifying patient conditions, predicting drug ratings, and performing sentiment analysis. We implemented and evaluated Convolutional Neural Networks (CNNs), Artificial Neural Networks (ANNs), and Recurrent Neural Networks … …Journal of Computer Science, Vol. 22, Issue 9 · 7 Sep 2026 · 736 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Machine Learning-Based Sentiment Analysis of Article 370 Tweets to Support Government Policy DecisionsSubhasis Mohapatra, Sudhir Kumar Mohapatra, Sweta Samantaray et al.This study proposes a robust sentiment analysis framework to evaluate public opinion on the abrogation of Article 370 using Twitter data. The methodology begins with tweet collection through the Twitter API, followed by systematic preprocessing. Sentiment labels were generated using the Text Blob lexicon-based polarity scoring approach to facilitate the construction of a large-scale sentiment dataset. Features are extracted, and … …Journal of Computer Science, Vol. 22, Issue 6 · 2 Jul 2026 · 914 accessesView PDFCite
Research ArticleOpen accessIn the abstractEnhancing Sentiment Analysis for Malayalam With mBERT: A Profoundly Transparent and Accurate Approach Using LIMEAnitha R., K. S. Anil Kumar, Rajeev R. R. et al.The overlapping sentiment boundaries, intensifiers, and intricate morphological structures in Malayalam present particular difficulties for sentiment analysis, making it hard for traditional machine learning techniques to produce consistent results. We present an explainable sentiment analysis framework in this paper that refines a Multilingual Bidirectional Encoder Representations from Transformers (mBERT) model on a novel constituency-level dataset that has been manually curated … …Journal of Computer Science, Vol. 22, Issue 5 · 2 Jun 2026 · 1,061 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Context Aware Deep Learning Framework for Multi-Level Arabic Fake News Detection Using Hybrid Linguistic RepresentationsNoor Mahmoud Alkudah, Somia Abufakher, Raja Masadeh et al.The rapid spread of false information on social media has made it even more important to be able to spot false news, especially in Arabic-speaking areas where language is more complicated and news is organized in a hierarchy. Recent research show that deep learning and transformer-based models work well, but most of them only look at performance metrics and don't … …Journal of Computer Science, Vol. 22, Issue 3 · 27 Mar 2026 · 1,566 accessesView PDFCite
Research ArticleOpen accessIn the abstractAraSenti-MARBERT-DynGCN: An Advanced Framework for Sarcasm Detection in Arabic TextBassma M Mousa, Mohammed H. Haggag, Mervat GheithSarcasm detection in Arabic texts is challenging because of the complexity in Arabic morphology, the multitudes of dialects used by native speakers, and its strong reliance on context. The lack of standardized orthography in most written forms of Arabic, combined with the frequent use of colloquialisms and metaphorical expressions, makes the task all the more difficult when trying to detect … …Journal of Computer Science, Vol. 21, Issue 11 · 12 Feb 2026 · 1,562 accessesView PDFCite
Research ArticleOpen accessIn the abstractClassifcation of Social Media Posts X For Mental Health Symptoms Identification Using NLP Techniques and Transformers ModelAndika Dwi Asmoro Wicaksono, RojaliThe increasing use of social media has enabled large-scale analysis of user-generated content to monitor mental health trends. This study focuses on sentiment prediction of mental health-related posts on platform X using transformer-based models, specifically IndoBERT, DistilBERT, and IndoRoBERTa. The goal is to evaluate the effectiveness of these models in classifying social media posts into positive, negative, and neutral sentiment … …Journal of Computer Science, Vol. 22, Issue 1 · 11 Feb 2026 · 1,851 accessesView PDFCite