Geo-Spatial Analysis of Information Outreach in Twitter Social Network

With the expansion of social media at a very degree, analysis of user interest, influence, popularity etc. has become essential using the available data. A large amount of information about the twitter user can be extracted using twitter API according to the requirement for the analysis. Millions of users spread their opinions around the world by posting tweets on daily basis. This model aims to develop an application that creates the network of any particular twitter user using mention-based anomaly and state the most active users and influencers based on two different criteria in the network. It also aims at geospatial analysis to study the virality of the trend spread by the user throughout the world. This model extracts the top mentioned usernames from the user tweets and custom them to create the network. The projected model assist user in finding influencers in their network so that the information can be made to spread through them and also depicts their reach and connections. The model also proposes a formula for finding the most active users in the network. Diverse visualization methods are used to demonstrate the analysis of mentioned usernames, network model and for geospatial analysis using various python packages.