Real-time geo influence in social networks

Exponential burst of real-time information generated through Social Media Networks in recent years, creates a hot ubiquitous platform for research among data scientists. Main area under spotlight in Social Networks Analysis (SNA) is friendship networks, user influence and computation of how deep and how fast the information diffuses. Amidst recent upsurge in Smartphone usage statistics, there is spectacular rise in tagging of feeds and post them with locations due to GPS localizations (Geo-tags and location coordinates of images and news feeds). For the local advertisers and social campaigners, it is vital to carve out phase based user reach models in a particular city/location. In this paper, an algorithm to calculate real-time geo influence of twitter users pertaining to location and time constraints is proposed and necessitate its requirement to meet the vital requisite to find out how fast information is spread by a particular user in a certain city/area and hence providing a platform for ranking them based on their influence in a particular place, and measuring speed of information travel. Subject Descriptors-Data mining and social computing, Social and Behavioural Sciences.