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14 articles for “Real-Time Sentiment Analysis”
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Emote_X: An AI-Driven Framework for Real-Time Twitter Sentiment Classification Using Machine Learning
Abstract: Social media has become one of the ways people share their thoughts, feelings and responses to what is happening in the world. Twitter, which is now called X is an example. It creates a constant flow of short messages. These messages contain clues about how people feel in areas like business, health care, politics, entertainment and when there is a disaster. Tweets are very messy. They have abbreviations, hashtags, emojis, …
Published in Journal of Computer Technology & Applications · Vol. 17, Issue 3, 2026 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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Real Time Analysis of Twitter Data
Abstract: In last two decades, big data has emerged as one of the most trending fields of research. In today’s world, every minute, huge amount of structured and unstructured data is produced via various platforms. This data includes texts, images, and forums gathered from social media platforms. This increasing data implies a fundamental change in the way we analyze data since it is unable to analyze data using conventional methodologies and …
Published in Current Trends in Information Technology · Vol. 6, Issue 1, 2016 · pp. 6–14 Read article
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Virtual Job Assistance
Abstract: In today’s competitive job market, interviews are a critical gateway to employment, but many candidates struggle with effective preparation. Traditional methods, such as mock interviews with friends or career counselors, often fail to provide detailed feedback or replicate real-world interview dynamics. The “AI-Powered Virtual Job Interview Simulator” addresses these challenges by leveraging advanced technologies, such as Natural Language Processing (NLP), to create a realistic and engaging environment for interview practice. …
Published in Journal of Mechatronics and Automation · Vol. 12, Issue 3, 2025 · pp. 1–11 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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Sentiment Analysis Based Telecom Churn Prediction
Abstract: Predicting customer churn is a big challenge and a survival basic for Telecom operators. In a large and competitive market like India, it is very essential to gather real-time customer feedback as a health indicator. Social networks have evolved as a rich source of real-time sentiments and opinions of the general public. In this research, tweets for the Twitter handle of 5 major telecom brands in India: Aircel, Bharti Airtel, …
Published in Journal of Web Engineering & Technology · Vol. 7, Issue 1, 2020 · pp. 6–12 Read article
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Twitter based TV Rating Analysis with TV-viewing and Sentiment Analysis
Abstract: Social Media is now used as a back channel to TV programs by viewers who would like to express their opinion about watching programs or just simply put on records of TV viewing. TV viewing rate is a critical indicator regarding the popularity of programs.Now a day’s social media is generally used to gather crowd sentiments to gather this information. Current methodologies based on Neilsen TV ratings adopt small sample …
Published in Current Trends in Information Technology · Vol. 4, Issue 1, 2014 · pp. 21–28 Read article
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Sentimental Analysis of Twitter Data
Abstract: Today, the world is rapidly heading towards the digital lifestyle. The data volume is getting larger and larger day by day. The solution for this problem can be resolved with the help of latest technology called as “Hadoop”. The data can be stored, processed, analyzed and later the results can be visualized. Here, in this paper, we are studying to fetch real time data from a social networking site, i.e. …
Published in Journal of Web Engineering & Technology · Vol. 6, Issue 1, 2019 · pp. 52–57 Read article
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Harnessing Machine Learning for Stock Movement Prediction: A Review of Current Approaches
Abstract: Stock price prediction is a crucial task in financial analysis, aiding investors and traders in making informed decisions. This study investigates the use of deep learning methods, particularly Long Short-Term Memory (LSTM) networks, for predicting stock prices based on historical market data. The dataset, sourced from Yahoo Finance, consists of time-series stock price data, which is preprocessed, feature-engineered, and visualized to improve prediction accuracy. The model's performance is assessed using …
Published in Journal of Advances in Shell Programming · Vol. 12, Issue 2, 2025 · pp. 29–40 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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Enhancing Customer Engagement with AI-Driven Movie Recommenders: Integrating Neural Collaborative Filtering, Sentiment Analysis, and Conversational Agents
Abstract: In today’s competitive digital landscape, user engagement is a critical factor for the success of entertainment platforms, especially those offering movie recommendations. This study introduces a comprehensive AI-driven framework designed to enhance customer interaction, satisfaction, and loyalty through the intelligent integration of multiple deep learning models. The system combines three core components: Neural Collaborative Filtering (NCF) for generating personalized movie recommendations based on user behavior and preferences, Long Short-Term Memory …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 3, 2025 · pp. 45–54 Read article
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Optimizing Customer Care Centre Performance: A Data Analytics Approach
Abstract: Customer care centres are essential in today's competitive corporate environment for ensuring client loyalty and satisfaction. By utilizing data analytics approaches, one may gain important insights regarding performance overall, operational effectiveness, and customer interactions. Data analytics encompasses the analysing, interpretation, and extraction of valuable insights from data to aid decision-making and address intricate issues. Call centre analytics is the process of gathering and evaluating call data to assist companies in …
Published in Recent Trends in Programming languages · Vol. 11, Issue 1, 2024 · pp. 34–49 Read article
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Depression Detection Using AI with Chatbot Support
Abstract: Depression is a major global health concern and a significant contributor to suicide rates worldwide. India reports a high number of suicide cases, making the early detection of mental distress and depression essential for timely intervention. This research presents an AI-based system for depression detection that integrates deep learning, natural language processing (NLP), and a chatbot for user support. The system analyzes facial expressions using convolutional neural networks (CNNs) and …
Published in Research & Reviews: A Journal of Embedded System & Applications · Vol. 14, Issue 1, 2025 · 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