Text fotograph match analysis with text data mining technics for compiled posts which include fotograph through social media

Increasing internet usage day by day created social platforms in which people can interact with each other through internet. In these platforms, thousands of people can share visual and textual posts at the same time as using visual and textual co mmunication instead of auditory communication. A shared post falls into interaction areas like groups which the sharing individual registered for, his followers and friends so that it can fall before of the groups he involved in, his followers and friends as well as a group, an individual or individuals who he does not know as an interaction. Therefore a post can reach millions of people by only one sharing. In this thesis, it is conducted that whether or not there is a relationship between texts and photog raphs which are shared through these platforms in which interaction is made as visual and textual. Initially, data is drawn from social platforms with specially developed software for this particular thesis. The photographs of the drawn data are analyzed in color analysis software which is developed for this particular thesis. Color analysis program conducted color weighting as analysis each pixel of each photograph. Data which is drawn and completed color analysis phase is transferred to data analysis pro gram. Knime is utilized as data analysis program. The transferred data is classified with decision tree. Lastly, estimations are made through classified data