Welcome to IJSDR UGC CARE norms ugc approved journal norms IJRTI Research Journal | ISSN : 2455-2631
International Peer Reviewed & Refereed Journals, Open Access Journal
ISSN Approved Journal No: 2455-2631 | Impact factor: 8.15 | ESTD Year: 2016
Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.15 (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: August 2022

Volume 7 | Issue 8

Impact factor: 8.15

Click Here For more Info

Imp Links for Author
Imp Links for Reviewer
Research Area
Subscribe IJSDR
Visitor Counter

Copyright Infringement Claims
Indexing Partner
Published Paper Details
Paper Title: Predicting the Disease Out Breaks Using Social Networks
Authors Name: G.Lakshmi , A Haritha , PV Naveen Kumar , Y.N.S. Ayyappa
Unique Id: IJSDR1606066
Published In: Volume 1 Issue 6, June-2016
Abstract: Data is being produced colossally on social media, a platform where people voice their experiences & opinions on varied contexts. Health Care being one of them, topics like health conditions, their symptoms, treatments, side effects, and so on will be discussed inevitably. This makes the publicly available social media data an invaluable resource for mining such data to discover interesting and actionable healthcare insights. The main objective of our project is to reduce the impact of seasonal influenza epidemics. We present the method, which monitors messages posted on Twitter with a mention of flu indicators to track and predict the emergence and spread of an influenza epidemic in a population. Based on the data collected during 2 weeks from 20th December 2015.The analysis results will subsequently reported visually in terms of, distribution of flu types, flu symptoms, and flu treatments. This method can be very useful for early prediction of flu outbreaks, which in turn can facilitate faster and better response preparation.
Keywords: Tokenize and Stopwords, Correlation Analysis, WordCloud, Twitter
Cite Article: "Predicting the Disease Out Breaks Using Social Networks", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.1, Issue 6, page no.380 - 384, June-2016, Available :http://www.ijsdr.org/papers/IJSDR1606066.pdf
Downloads: 000101773
Publication Details: Published Paper ID: IJSDR1606066
Registration ID:160562
Published In: Volume 1 Issue 6, June-2016
DOI (Digital Object Identifier):
Page No: 380 - 384
Publisher: IJSDR | www.ijsdr.org
ISSN Number: 2455-2631

Click Here to Download This Article

Article Preview

Click here for Article Preview

Major Indexing from www.ijsdr.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

Track Paper
Important Links
Conference Proposal
DOI (A digital object identifier)

Providing A digital object identifier by DOI
How to GET DOI and Hard Copy Related
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
Social Media

Indexing Partner