Search
9 articles for “Twitter (now X)”
-
Sentiment Analysis of X (Formerly Twitter) Using Machine Learning
Abstract: Sentiment analysis is a methodology to determine the nature and behavior of each and every user for the content posted on the social media platform in the form of post and feed. Consumers of the online platform are encouraged to post reviews of the product that they purchase. Little attempt is created by Amazon to confine or limit the content of these reviews. The number of reviews for various merchandise …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 11, Issue 2, 2024 · pp. 28–37 Read article
-
Deep Learning-Based Sentiment Analysis of Twitter COVID-19 Vaccination Responses
Abstract: The COVID-19 pandemic has caused significant fear, anxiety, and complex emotions or feelings in a large number of people. A global vaccination campaign to end the SARS-CoV-2 epidemic is now in progress. People's feelings have become more complex and varied since the introduction of vaccinations against the coronavirus. The use of social media platforms such as X (formally known as Twitter) enables users to communicate with one another and share …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 10, Issue 3, 2023 · pp. 1–14 Read article
-
Online Hate Speech on Social Media Platforms
Abstract: Social media is an online interactive digital platform which allows large number of group of people to connect with each other virtually, to create content and share their thoughts, information, ideas, and much more in the form of text, pictures, and videos. But sometime people share their negative view, and their message is turned into hate speech. Hate speech is of two types: online and offline. Online hate speech spreads …
Published in International Journal of Mobile Computing Technology · Vol. 2, Issue 1, 2024 · pp. 16–25 Read article
-
A Supervised Learning Approach for Toxic Comment Detection on Social Media Platforms
Abstract: Nowadays everyone uses social media platforms like X (formerly Twitter), Instagram, Facebook, etc. for various purposes. With the help of this, we share our opinions, ideas, and feelings. Generally, the datasets obtained from the internet are constructive; however, there is a significant proportion of toxic ones. The datasets are filtered to remove noise, and noise is removed in post-processing. The study initiates with the upload and preprocessing of a toxic …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 11, Issue 2, 2024 · pp. 7–14 Read article
-
Social Media’s Impact on Youths’ Physical and Online Political Engagement
Abstract: Young people are thought to belong to the age group that is least interested in politics and political issues. It is a socially desirable objective to raise young people’s political participation, given that they will be the ones influencing politics in the future. More youthful ages were principally influenced by the coming of the web and new media, and almost certainly, new media — like informal communities — will keep …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 11, Issue 2, 2024 · pp. 15–20 Read article
-
Unleashing the Power of Mathematics in Natural Language Processing: Sentiment Analysis Perspectives
Abstract: Sentiment analysis (SA), which utilizes natural language processing (NLP), computational linguistics, text analysis, image processing, and video processing to extract and analyze subjective information from the internet, social media, and other sources, is becoming increasingly popular in both the business world and the scientific community. It is even possible to model it so that it focuses on polarity, sentiments and emotions, urgency, and even goals. It is able to distinguish …
Published in Recent Trends in Programming languages · Vol. 10, Issue 2, 2023 · pp. 1–9 Read article
-
Tweets Classification using Different Classifiers for Sentiment Analysis
Abstract: Twitter is a famous platform for social networking where people share and engage with "tweets" comments. It is a way of expressing people's opinions or emotions on various topics. Different parties, like producers and consumers, have carried out a sentiment analysis on tweets to gain insights into goods or to analyze the sector. Also, the accuracy of our sentiment analysis forecasts will increase with the recent advances in machine learning …
Published in Research & Reviews : Journal of Statistics · Vol. 10, Issue 3, 2021 · pp. 34–43 Read article
-
Enhancing Profanity Detection in Dravidian Languages: Leveraging Language Models for Optimization and Improvement
Abstract: Detecting and documenting instances of abusive behaviour can significantly improve the quality of virtual environments. Given the vast amount of content published daily on social media, it is impractical for human annotators to manually identify potentially harmful content. Recent algorithmic initiatives, especially on platforms like Twitter, have advanced in abuse detection. However, for Dravidian texts, there remains a need to understand the context better and build robust language models for …
Published in Recent Trends in Programming languages · Vol. 11, Issue 2, 2024 · pp. 17–23 Read article
-
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