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International Journal for Research Trends and Innovation
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ISSN Approved Journal No: 2456-3315 | Impact factor: 8.14 | ESTD Year: 2016
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Issue: December 2025
Volume 10 | Issue 12
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Impact Factor : 8.14
Issue per Year : 12
Volume Published : 10
Issue Published : 115
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| Paper Title: | Sentiment Analysis on Social Media Post |
| Authors Name: | Deepan Chandru |
| Download E-Certificate: | Download |
| Author Reg. ID: |
IJRTI_200395
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| Published Paper Id: | IJRTI2501057 |
| Published In: | Volume 10 Issue 1, January-2025 |
| DOI: | |
| Abstract: | With the rapid growth of social media platforms, the volume of user-generated content has increased significantly, offering valuable insights into public opinion and sentiment on various topics. Twitter, a leading social media platform, has emerged as a critical space where individuals express their thoughts and emotions in real-time. This project focuses on the application of sentiment analysis to Twitter data, aiming to classify tweets into positive, negative, and neutral sentiments. The primary objective is to create a robust sentiment analysis model that leverages machine learning techniques such as Logistic Regression to analyze the sentiment behind social media posts. The sentiment analysis model is trained using a dataset consisting of millions of tweets, which are pre-processed to remove noise and perform text stemming. Additionally, contextual factors such as hashtags, user mentions, and emoticons are considered to enhance the accuracy of sentiment detection. One of the challenges addressed in this study includes handling Twitter-specific nuances, such as the short length of tweets and the evolving language on the platform, including the use of slang and sarcasm. To ensure effective deployment, a web-based interface has been developed, allowing users to input text and receive real-time sentiment analysis results. This interactive website demonstrates the model’s functionality, presenting users with sentiment classifications and enabling actionable insights. The findings from this project can be applied in various domains, such as market research, brand management, political analysis, and real-time event monitoring, helping organizations understand public sentiment. |
| Keywords: | we aim to provide a scalable and accurate solution for sentiment analysis on Twitter, offering valuable insights that can influence decision-making across multiple industries. |
| Cite Article: | "Sentiment Analysis on Social Media Post ", International Journal of Science & Engineering Development Research (www.ijrti.org), ISSN:2455-2631, Vol.10, Issue 1, page no.a448-a482, January-2025, Available :http://www.ijrti.org/papers/IJRTI2501057.pdf |
| Downloads: | 000592 |
| ISSN: |
2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
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Published Paper ID: IJRTI2501057
Registration ID:200395
Published In: Volume 10 Issue 1, January-2025
DOI (Digital Object Identifier):
Page No: a448-a482 Country: Chennai, Tamil Nadu, India Research Area: Science & Technology Publisher : IJ Publication Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2501057 Published Paper PDF: https://www.ijrti.org/papers/IJRTI2501057 |
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ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED,
Journal Starting Year (ESTD) : 2016
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