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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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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

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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
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IJRTI_183657
Published Paper Id: IJRTI2208143
Published In: Volume 7 Issue 8, August-2022
DOI:
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 (www.ijrti.org), ISSN:2455-2631, Vol.7, Issue 8, page no.825 - 830, August-2022, Available :http://www.ijrti.org/papers/IJRTI2208143.pdf
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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 : https://www.ijrti.org/viewpaperforall?paper=IJRTI2208143
Published Paper PDF: https://www.ijrti.org/papers/IJRTI2208143
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ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED
Journal Starting Year (ESTD) : 2016

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