Abstract
Data science is a concept to unify statistics, data analysis and their related methods in order to understand and analyze actual phenomena with data. The common use of Online Social Networks (OSN)[2] for networking communication which authorizes real-time multimedia capturing and sharing, have led to enormous amounts of user-generated content in online, and made publicly available for analysis and mining. The efforts have been made for more privacy awareness to protect personal data against privacy threats. The principal idea in designing different marketing strategies is to identify the influencers in the network communication. The individuals influential induce “word-of-mouth” that effects in the network are responsible for causing particular action of influence that convinces their peers (followers) to perform a similar action in buying a product. Targeting these influencers usually leads to a vast spread of the information across the network. Hence it is important to identify such individuals in a network, we use centrality measures to identify assign an influence score to each user. The user with higher score is considered as a better influencer.
Highlights
To identify influencers on social network sites like twitter, we have described in step wise extraction method is used to map users network
IPython Console: Each page analysed is requested by the program from Twiter API
The current image shows the execution of a tweet
Summary
Centrality: It means there is no unanimity in measuring the market and its network progress. N is total number of nodes in a network, a = adjacency matrix if a(i,j)==1, node i is connected to node j. The simplest computation of closeness centrality σC can be represented as follows: where dG(i, j) is the number of links in the geodesic distances from node i to node j. Eigen vector centrality (EC) when compared to Direct Centrality (DC), takes into account the number of direct links and indirect contacts in the network. Eigen vector X(i,G) is given as follows: Any social network like Twitter, Facebook, Watsapp markets business since this sites provide real-time data for business insiders. The interconnectedness in Fig.[2] shows relationships between actors to show business how important it is to find more influencers and understand their requirements. Centrality From the above fig.[2], we can understand the performance and evaluation of centrality depends on Observation, Orientation, Decidability and Actions
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