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Submitted by: Janki Adhvaryu (pt200614) Mayank Singh Sakla (pt200814)
Using social media data for analysis of EBOLA
Introduction
Ebola viral disease (EVD),also known as Ebola hemorrhagic fever(EHF)
It is a serious, infectious viral hemorrhagic fever (VHF) Humans, monkeys,gorillas, chimpanzee suffers by the this virus of
filoviridae family . It is deadly virus with 90%deaths of all infected people. Symptoms of Ebola: poor liver function fever & severe weakness headache & Muscle pain After 8-10 days condition of symptoms becomes severe: Bleeding, low white blood cells, low platelet counts, impaired kidney
Objective:
To study the geo-linked information of Ebola in social media:
Identifying Ebola hotspot based on location. Information propagation in crisis situation Integrating the social media data for analysing
geographical or spatial distribution of diseases.
• Twitter• Facebook• World health organization• Ministry of health• Google news
Our study is totally based on Twitter as a source
Data Source
Data collection
Data extraction
Data analysis
Desired output
Human Situation analysis
Data at stream rate Comparable rate Data consolidationMethodology
From data source (Query feed.net)
Comparable data extracted
Prepared relational database
Maps showing different aspects
Behavioral pattern throughout world
Our search criteria in twitter are • #Ebola victims• #Ebola cause• #Ebola outbreak• #Ebola
Relational Database includes:
Table Attribute
Location City , country
Platform Twitter
Post Description of post
User Username
For our analysis and output we have run query on this databaseWe have also used ArcGIS as a tool
Output Output map is showing the countries which are in
relation with Ebola worldwide
Output
Among 81 countries which are in relation with Ebola tweets; we have obtained 75 countries with single tweets.
Liberia ,sierra leone, Guinea are having higher percent of tweets.
Output
Output map is showing the location of the cities.
By analyzing spatial distribution-clustering and scattering of tweets can be understood.
Output Search criteria is EBOLA OUTBREAK
We have got location of cities. Analysis shows- The geographical spread of Ebola outbreak city is in proximity of 5000km from highly affected countries.
OutputFrom post content we extracted number or tweets per states.
The output map is showing the concentration of tweets.
OutputAfter reading post content of India and Philippines. it results into how the travel of Ebola to that country.
Source: Google news and twitter post contents.
Reference:http://www.queryfeed.net/http://news.google.co.in/
Software used:ArcGIS10.2.2 Ms Access
Thank you