UGC CARE norms ugc approved journal norms IJRTI Research Journal

Click Here

International Journal for Research Trends and Innovation
International Peer Reviewed & Refereed Journals, Open Access Journal
ISSN Approved Journal No: 2456-3315 | Impact factor: 8.14 | ESTD Year: 2016
Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.14 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI)

Call For Paper

For Authors

Forms / Download

Published Issue Details

Editorial Board

Other IMP Links

Facts & Figure

Impact Factor : 8.14

Issue per Year : 12

Volume Published : 7

Issue Published : 79

Article Submitted : 5528

Article Published : 3054

Total Authors : 7813

Total Reviewer : 540

Total Countries : 68

Indexing Partner


This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
Published Paper Details
Paper Title: Multimedia Sentiment Analysis On Public Social Network Using NLP
Authors Name: Lakshmi Janaki K , Swamy TN , Uma Maheswari P , Reshma D , Jayanth D
Download E-Certificate: Download
Author Reg. ID:
Published Paper Id: IJRTI2208143
Published In: Volume 7 Issue 8, August-2022
Abstract: Social Networks are the platforms that engage large number of users where the necessity of using sentiment analysis is highly critical. Sentiment is an approach used in natural language processing (NLP), sometimes known as opinion mining. It is the technique of identifying if multimedia, such as text, images, and coded communications, has positive or negative emotion. Usage of hate speech which includes sexist and racist comments that are likely to provoke issues between people or states or nations is high in public social networks. The main goal is to detect hate speech in public social networks like Facebook, Twitter, YouTube etc., that can be filtered and reported. The project proposes multimedia sentiment analysis on public social networks using natural language processing (NLP). The analysis is based on the Kaggle dataset which is a labelled dataset with the correct combinations of texts or messages and images and dataset collected from public accounts. The dataset is for each media is unique and provided in the form of a suitable file formats required for multimedia processing of data. This project filters out the messages using natural language processing technique not only in text but also in images. The messages will not be removed radically. The simulation is tested with python platform and various collaborative tools. The data is visualized and committed to provide the maximum accuracy and degree of usability to take decisions in real time without violating the user's freedom of thought.
Keywords: Multimedia, Sentiment Analysis, Natural Language Processing, Keras, ReLU, TF-IDF Vectorization, SMOTE, Class Imbalance
Cite Article: "Multimedia Sentiment Analysis On Public Social Network Using NLP", International Journal of Science & Engineering Development Research (, ISSN:2455-2631, Vol.7, Issue 8, page no.825 - 830, August-2022, Available :
Downloads: 000178211
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
Publication Details: Published Paper ID: IJRTI2208143
Registration ID:183657
Published In: Volume 7 Issue 8, August-2022
DOI (Digital Object Identifier):
Page No: 825 - 830
Country: Bangalore, Karnataka, India
Research Area: Computer Science & Technology 
Publisher : IJ Publication
Published Paper URL :
Published Paper PDF:
Share Article:

Click Here to Download This Article

Article Preview
Click Here to Download This Article

Major Indexing from
Google Scholar ResearcherID Thomson Reuters Mendeley : reference manager : cornell university library Research Gate CiteSeerX DOAJ : Directory of Open Access Journals
DRJI Index Copernicus International Scribd DocStoc

ISSN Details

ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED
Journal Starting Year (ESTD) : 2016

DOI (A digital object identifier)

Providing A digital object identifier by DOI.ONE
How to Get DOI?


Open Access License Policy

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License

Creative Commons License This material is Open Knowledge This material is Open Data This material is Open Content

Important Details

Social Media

Join RMS/Earn 300


Indexing Partner