A Twitter Social Media Modeling: Tesla’s First Fatal Crash Tweeting Behavior

In recent years, new social network data has been available due to adoption of new Information and Communication Technologies (ICT) that have allowed the development of social media networks. Twitter, as one of the most popular social networks around the globe, offers particularly large public data sets available by Twitter's RESTful Application Programming Interface (API) that allow developers to request through HTTP access to core Twitter data, including update timelines, status data, and user information. Through the development of a program script that specially run-time environment that automates the retrieve of Twitter information was possible to store and model a heterogeneous-multiplex network in Neo4j graph-databaseengine. The objective of this project is to be able to describe and explore the social media network topology from a specific business application. This was done by using Python and Neo4j modeling of social media interactions with the objective of understand social and behavioral relationships by social network analysis

AUTHOR: J.A. Sánchez Castro