 |
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)
|
Issue: October 2025
Volume 10 | Issue 10
Review Result and Publication of Paper within : 2-3 days
Click Here For more DetailsFor Authors
Forms / Download
Published Issue Details
Editorial Board
Other IMP Links
Facts & Figure
Impact Factor : 8.14
Issue per Year : 12
Volume Published : 10
Issue Published : 113
Article Submitted : 17997
Article Published : 7746
Total Authors : 20484
Total Reviewer : 747
Total Countries : 140
Indexing Partner
Licence
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
|
Published Paper Details
|
|
| Paper Title: | Identifying Fake News Using Real Time Analytics |
| Authors Name: | Pamidimukkala Pavani , Allari Tarun , Muppineni Gopi Krishna , Velagapudi Namita , C Karthikeyan |
| Download E-Certificate: | Download |
| Author Reg. ID: |
IJRTI_188467
|
| Published Paper Id: | IJRTI2311035 |
| Published In: | Volume 8 Issue 11, November-2023 |
| DOI: | |
| Abstract: | Identifying the fake news has been the field of the interest within the researchers and analysts for such a long period of time. News articles are so complicated to predict because of their higher volatile and unpredictable nature which is completely dependent on the factors like ever changing economic factors, political factors, change of the leadership in dominant places of the world and so on. Predicting the news originality depending up on the data that is already gathered which is named as the daily information alone has become not so sufficient to predict the ups and downs of the news. The studies and surveys that are already in existence in the field of data analysis have found that there is very complicated and undisturbed correlation between the daily human incidental movements and the publication of the news articles. Numerous analyses regarding the news originality studies have been conducted in order to attain the accuracy by utilizing many algorithms like naïve bayes regression, data analytics and also the deep learning. The accuracy of the models that run with the help of the data analytics methods are completely dependent on the amount of information provided for the sake of the training. The amount of the verbal data that is available and analyzed during few surveys and studies were considered to be insufficient and as a result the recognitions that are with low accuracy rates were observed. By gathering a sizable quantity of time series data and using data analytics models to analyze the data to forecast the originality of news stories, we attempted to increase the rate at which false news may be accurately identified in this research work. |
| Keywords: | Data Analytics; Artificial Neural Network; SVM; LSTM; Natural Language Processing; |
| Cite Article: | "Identifying Fake News Using Real Time Analytics", International Journal of Science & Engineering Development Research (www.ijrti.org), ISSN:2455-2631, Vol.8, Issue 11, page no.249 - 254, November-2023, Available :http://www.ijrti.org/papers/IJRTI2311035.pdf |
| Downloads: | 000205078 |
| 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: IJRTI2311035
Registration ID:188467
Published In: Volume 8 Issue 11, November-2023
DOI (Digital Object Identifier):
Page No: 249 - 254 Country: Guntur, Andhra Pradesh, India Research Area: Computer Science & Technology Publisher : IJ Publication Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2311035 Published Paper PDF: https://www.ijrti.org/papers/IJRTI2311035 |
| Share Article: | |
|
Click Here to Download This Article |
|
| Article Preview | |
|
|
|
Major Indexing from www.ijrti.org
| Google Scholar | ResearcherID Thomson Reuters | Mendeley : reference manager | Academia.edu |
| arXiv.org : 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? |
Conference
Open Access License Policy
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
Important Details
Join RMS/Earn 300
WhatsApp
Click Here
Click Here
Indexing Partner |
|||
| Copyright © 2025 - All Rights Reserved - IJRTI | |||