PESCAD_Storm

Big Data Directed Acyclic Graph Model for Covid-19 Event Stream Detection (Publication)
The aim of this work is to detect anomalous events associated with COVID-19 from Twitter. To this end, we propose a distributed Directed Acyclic Graph topology framework to aggregate and process large-scale real-time tweets related to COVID-19. The core of our system is a novel lightweight algorithm that can automatically detect anomaly events.

Using: Poisson Event Stream Collective Anomaly Detection (PESCAD) Algorithm

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APACHE STORM :

In Spout.java, please configure these lines:

String consumerKey = "PUT YOUR consumerKey HERE";
String consumerSecret = "PUT YOUR consumerSecret HERE";
String accessToken = "PUT YOUR accessToken HERE";
String accessTokenSecret = "PUT YOUR accessTokenSecret HERE";

VISUAL:

In map.php, please configure these lines:

accessToken: 'copy_your_access_token_here'
'access_key' => 'COPY_YOUR_ACCESS_KEY_HERE',

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Import the "Apache Storm" as a maven project.

Import the "test.sql" into a MySQL DB named "test".

Put the "visual" folder in your www or htdocs directory.