Gossip Management at Universities using Big Data Warehouse Model Integrated with a Decision Support System

Abstract

Big Data has recently been used for many purposes like medicine, marketing and sports. It has helped improve management decisions. However, for almost each case a unique data warehouse should be built to benefit from the merits of data mining and Big Data. Hence, each time we start from scratch to form and build a Big Data Warehouse. In this study, we propose a Big Data Warehouse and a model for universities to be used for information management, to be more specific gossip management. The overall model is a decision support system that may help university administraitons when they are making decisions and also provide them with information or gossips being circulated among students and staff. In the model, unsupervised machine learning algorithms have been employed. A prototype of the proposed system has also been presented in the study. User generated data has been collected from students in order to learn gossips and students’ problems related to school, classes, staff and instructors. The findings and results of the pilot study suggest that social media messages among students may give important clues for the happenings at school and this information may be used for management purposes.The model may be developed and implemented by not only universities but also some other organisations.

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