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3 articles for “Twitter Analytics”
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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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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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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