APPLICATION OF SOCIAL COMPUTING ANALYSIS VIA ATTITUDES OF MEDIA USERS

Abstract

Analyzing and modeling of social platforms and media data are rather developed and still developing today. Social behaviors are analyzed and characterized with social and artificial intelligence, statistical methods, analytical approaches and evolutionary algorithms. Data mining and machine learning are used in the social computing. In this study, social computing included, two surveys used a questionnaire with 43 different questions handed over in random sample to 537 different high school students in Istanbul. Social media attitudes of students were evaluated using J48 algorithm. According to J48 algorithm, which constitutes machine learning, learning took place for 14 questions out of 43. The analysis produced a Kappa Statistic (K) value of 0.446 and F-Measure of 0.701. A decision tree was created to support decision-making.