Identifying Effective Attributes for Structuring Circle/Lists in Social Media using R

Big Data refers to large amount of data generated from heterogeneous and autonomous resources. The data generated from social media aims in providing information about the individual and their respective behavior. The user attributes of user profile in the social data also provides a structure to form various social networks. This motivation of the work carried out in this paper focuses on analyzing the social data for finding attributes which are effective in making circles and lists in social media. Using various dimensions such as first_name, last name, school, place, location, birthday, degree, class, education etc the paper aims in providing the principle components which aids in building the social network. The paper employs Principal Component Analysis for the analysis of social media data for Circle/List formation. Principal Component Analysis is mathematical procedure to reduce number of dimensions of dataset by maintaining its original variability. The approach is utilized for isolating the attribute effective in making of circles. Interpretation and validation of the proposed methodology will be plotted by scree test in R programming environment.