sentiment analysis
26 articles · search the full text for this term
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Optimized Sentiment Analysis Through TextBlob and Hybrid RNN Models
Abstract: In today’s world, analyzing people’s feelings from what they write online has become very important. This is because there is a large amount of content created by users. To make this analysis accurate and fast, we present a method. This method uses a mix of two approaches: one that looks up words in a dictionary and another that uses computer learning. TextBlob is an affordable tool for getting an initial …
Published in International Journal of Computer Science Languages · Vol. 4, Issue 1, 2026 · pp. 29–28 Read article
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Comparative Study of BERT Variants for Sentiment Analysis with Error Analysis
Abstract: The use of media is going up fast in India, and this has led to the rise of Hinglish. Hinglish is an informal blend of Hindi and English that people commonly use in everyday conversations, especially across social media platforms such as Twitter, Facebook, and WhatsApp. People use Hinglish to talk to each other in a way that is not very formal. Hinglish blends English vocabulary with informal usage, often …
Published in International Journal of Computer Science Languages · Vol. 4, Issue 1, 2026 · pp. 39–48 Read article
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Understanding Sentiment Trends Through Zero-Shot and Few-Shot Learning Models
Abstract: The requirement for large, manually labeled datasets is one of the main barriers to applying sentiment analysis algorithms in specialized or rapidly evolving disciplines in the present natural language processing (NLP) landscape. This work investigates a paradigm shift from traditional fully supervised learning to data-efficient methods, specifically zero-shot learning (ZSL) and few-shot learning (FSL). This study uses the advanced capabilities of instruction-tuned large language models (LLMs), like GPT-4, to assess …
Published in International Journal of Computer Science Languages · Vol. 4, Issue 1, 2026 · pp. 01–08 Read article
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Explainable Sentiment Mining Model in Mental Health Forums for Emotion Classification and Justification
Abstract: Understanding and interpreting emotions expressed in online mental health discussions plays a crucial role in enabling early detection of psychological distress and facilitating timely interventions. As individuals increasingly turn to digital platforms to share personal experiences and seek support, automated systems capable of accurately identifying emotional states can significantly assist clinicians, moderators, and support communities. This paper presents a deep learning–based sentiment mining and emotion classification framework specifically designed to …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 4, Issue 1, 2026 · pp. 22–32 Read article
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Machine Learning Based Sentiment Analysis of Student Feedback in Higher Education
Abstract: Educational institutions routinely collect feedback from students to understand their perceptions of academic programs, infrastructure, and campus facilities, to improve the overall quality of the college environment. In current practice, feedback is often gathered using numerical or grade-based rating systems, which tend to oversimplify student opinions and may overlook important details related to their level of satisfaction. In contrast, open-ended textual feedback allows students to clearly express their views, concerns, …
Published in International Journal of Data Structure Studies · Vol. 4, Issue 1, 2026 · pp. 01–10 Read article
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AI-Enabled Feedback Management for Enhancing Education
Abstract: Institutions are becoming more aware of the importance of student input in improving learning experiences in the current educational environment. However, the intricate and complex patterns found in this feedback are frequently missed by conventional techniques like manual reviews and simple statistics. Our proposal suggests a novel method for analyzing student input and more accurately predicting sentiment by utilizing Long Short-Term Memory (LSTM) algorithms. We can learn more about student …
Published in International Journal of Electronics Automation · Vol. 3, Issue 2, 2025 · pp. 21–27 Read article
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Evaluating the Efficiency of LLMs-SA (Sentiment Analysis) via Social Media Texts
Abstract: Sentiment analysis (SA) is becoming popular in business and scientific communities as the processing of natural language (NLP), computational linguistics, text analytics, image-based processing or video- based processing is used in extracting and mining subjective information in the web, social network, etc. It is able to detect positive, negative or neutral information and can be selected to absorb polarity, sentiments, urgency and goals of mount importance. The majority of the …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 3, 2025 Read article
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Aspect-Based Sentiment Analysis Using a Hybrid Approach with Dependency Parsing
Abstract: The rapid expansion of digital communication has resulted in an unprecedented volume of consumer-generated textual data across online reviews, social media platforms, forums, and e-commerce websites. Extracting meaningful insights from this data is increasingly important for organizations seeking to understand customer opinions, preferences, and behavioral trends. Despite significant advances in sentiment analysis, many existing approaches primarily focus on surface-level features and often overlook deeper syntactic and semantic relationships within text. …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 4, Issue 1, 2026 · pp. 01–09 Read article
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Designing an AI-Based Platform for Stock Market Prediction
Abstract: The AI-Based Platform for Stock Market Prediction is an advanced tool designed to forecast stock prices and market trends using artificial intelligence. This platform combines machine learning algorithms, real-time financial data, and sentiment analysis to provide investors with actionable insights. The platform uses advanced predictive techniques like Long Short-Term Memory (LSTM) networks and Gradient Boosting Machines to generate precise and reliable forecasts. Additionally, it incorporates interactive visualizations and portfolio optimization …
Published in E-Commerce for Future & Trends · Vol. 12, Issue 3, 2025 · pp. 14–19 Read article
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AI-Powered Chatbot with Sentiment Analysis, Summarization, and Q&A for Business Automation
Abstract: Artificial Intelligence (AI) chatbots have become increasingly significant in recent years due to their ability to automate a wide range of business operations, improve user interaction, and create more efficient customer support experiences. The development of such systems goes beyond simple rule-based responses and now integrates advanced natural language processing (NLP) techniques to deliver contextually relevant and human-like interactions. This study introduces a chatbot framework that incorporates three major components: …
Published in Journal of Open Source Developments · Vol. 12, Issue 3, 2025 · pp. 01–05 Read article
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Real-time Emotion-aware AI Counseling System with Memory Retention Polymer Composites
Abstract: The availability of mental health services is still a major barrier, with many individuals constrained by financial limitations, social stigma, and a shortage of accessible counselors. This work introduces an emotion-aware AI counselor designed to provide empathetic and personalized emotional support via voice-based interfaces. The system leverages Natural Language Processing (NLP) and sentiment analysis to detect emotional cues from speech and generate contextually appropriate, comforting responses. A key innovation is …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 1395–1407 Read article
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AI-Based Sentiment Analysis of Public Perception Under Bangabandhu Sheikh Mujibur Rahman
Abstract: Sheikh Mujibur Rahman, known as Bangabandhu, played a pivotal role in Bangladesh’s post-liberation period (1971–1975). Understanding public sentiment during his leadership is crucial for historical analysis. This study employs Artificial Intelligence (AI)-based Sentiment Analysis to examine public perception through archived newspapers, parliamentary speeches, and historical records. Using Natural Language Processing (NLP) techniques, including sentiment classification and opinion mining, we analyze textual data to assess the prevailing public mood during his …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 3, Issue 2, 2025 · pp. 21–29 Read article
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ML Model Comparison for Sentiment Analysis Across Diverse Datasets
Abstract: Analyzing sentiment is crucial for understanding public opinion on various issues in marketing, politics, and social sciences. This study compares the performance of seven different machine learning algorithms for sentiment classification, focusing on their effectiveness, accuracy, and complexity. The research is conducted on a pre-processed dataset with balanced text samples, utilizing feature extraction methods such as Term Frequency-Inverse Document Frequency (TF-IDF). The performance assessment criteria consist of accuracy, precision, recall, …
Published in Journal of Operating Systems Development & Trends · Vol. 12, Issue 2, 2025 · pp. 26–33 Read article
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Forecasting Commodity Prices Using Deep Learning Techniques: An Empirical Evidence from India
Abstract: Commodity price forecasting is instrumental in financial markets, providing framework for investment choices and risk management practices. Traditional models, including statistical and machine learning approaches, have limitations in capturing the nonlinear and volatile nature of commodity prices. Deep learning (DL) techniques have emerged as promising alternatives, leveraging advanced neural networks to enhance predictive accuracy. This study presents a thorough and comprehensive examination of deep learning applications in commodity price prediction, …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 3, 2025 · pp. 08–12 Read article
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AI-Driven Product Management Assistants: Co-Pilot or Competitor for the Future PM?
Abstract: The emergence of Artificial Intelligence has led to a big transformation in the field of product management. When AI first came into picture, it was limited to the routine tasks but now AI assistants are able to handle a lot of decision making and streamline the execution process involved in product management. A major question with this emerging technology: can these assistants now or in future handle the work of …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 2, 2025 · pp. 58–63 Read article
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Optimizing Sentiment Analysis with Naïve Bayes and Random Forest Techniques: A Result-based Approach
Abstract: In the increased digitalization, the sentiment analysis and classification have evolved as an eminent area to determine the polarity of positive, negative, and neutral reviews of the customers and users on products. It is an integral application field that employs supervised learning, Machine Learning, and Natural Language Processing concepts. The proposed Semantic Analysis and Classification using Naive Bayes and Random Forest system accomplishes the sentiment polarity by classifying the user …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 2, 2025 · pp. 46–57 Read article
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Punjabi Text Sentiment Analysis Using Indic NLP
Abstract: Sentiment Analysis has become one of the challenging domains with the gaining popularity of Internet and social media platforms. Sentiment or opinion mining means to know people’s opinion, attitude, views and emotions towards anything. Sentiment analysis in English language has already been analyzing but there is a need of analyzing sentiments in other regional language in which Punjabi language is one of them. Users from the Punjab state of India …
Published in OmniScience: A Multi-disciplinary Journal · Vol. 15, Issue 1, 2025 · pp. 38–42 Read article
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Data Mining for E-Commerce and Social Media: Insights and Future Research Directions
Abstract: The fast expansion of e-commerce and social media has heralded a new era of data-rich settings, with enormous quantities of user interactions, preferences, and transactions generated on a daily basis. Data mining has developed as a critical strategy for leveraging big datasets, allowing businesses to gain concrete knowledge and drive decision-making. Data mining in e-commerce improves operational efficiency and user pleasure by allowing for personalized recommendations, consumer segmentation, fraud detection, …
Published in E-Commerce for Future & Trends · Vol. 12, Issue 1, 2025 · pp. 14–23 Read article
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Sentiment Analysis of E-Commerce Reviews using Machine Learning
Abstract: In e-commerce, sentiment pertains to the emotional responses, opinions, or perceptions that customers have about their online shopping experiences, including factors like product quality, service, and various processes such as ordering, shipping, and customer support. Sentiment analysis, which involves machine learning techniques, plays a crucial role in deciphering these sentiments. By using sentiment analysis, companies can obtain valuable insights from customer feedback from diverse online sources, including social media, surveys, …
Published in Journal of Operating Systems Development & Trends · Vol. 11, Issue 3, 2024 · pp. 25–37 Read article
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Social Media Analysis Using Big Data
Abstract: Social media has become an essential aspect of everyday life across different age groups, serving functions ranging from sharing personal updates to staying informed about social developments. Our objective is to harness big data to extract meaningful insights from the immense and ever-expanding volume of data generated on social media platforms. We will collect and analyze data from various social media sources, including text, images, and user interactions, using cutting-edge …
Published in Journal of Advanced Database Management & Systems · Vol. 11, Issue 3, 2024 · pp. 35–46 Read article