Periodicals of Engineering and Natural Sciences ISSN 2303-4521 Vol.6, No.1, June 2018, pp. 215~228 Available online at: http://pen.ius.edu.ba DOI: 10.21533/pen.v6i1.287 215 Data Science: Identifying influencers in Social Networks Srikanth Bethu 1 , V Sowmya 2 , B Sankara Babu 3 , G Charles Babu 4 , Y.Jeevan Nagendra Kumar 5 1,2,3 Departement of Computer Science and Engineering, GRIET, JNTU Hyderabad, Telangana, India 4 Departement of Computer Science and Engineering, Mallareddy Engineering College, JNTU Hyderabad, Telangana, India 5 Departement of Information Technology, GRIET, JNTU Hyderabad, Telangana, India srikanthbethu@gmail.com, sowmyaakiran@gmail.com, bsankarababu81@gmail.com, charlesbabu26@gmail.com, jeevannagendra@gmail.com Article Info ABSTRACT Article history: Received Jun 12 th , 201x Revised Aug 20 th , 201x Accepted Aug 26 th , 201x 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. Keyword: Data Analysis and Mining Data Science Online Social Networks Network communication Corresponding Author: First Author, Departement of Computer Science and Engineering, National Chung Cheng University, GRIET, JNTU Hyderabad, Telangana 500090, India. Email: srikanthbethu@gmail.com 1. Introduction Now a day’s Social Networks plays a communication media in real time for the user’s interaction. They are used to share all the experiences and their personal valid opinions on various topics like news, politics, celebrities, sports, events and products. In this way online social network has become important resource for knowledge sharing and knowing. For brand communications like Fashion industry, it exhibits high potential in digital marketing for integral growth. Now it has become brand ambassador for its messages and promotions to produce awareness among audience through continuous brand advertisement activities. The existing relations in a social network are as follows:  Similarities depending on demographic characteristics, locations or group memberships attributes of any two nodes.  The interaction relationships like speaking; chatting refers to continuous exchange of information between all the actors or users.