“Big Data Mining and Visualization over online Social Networks”
The explosive growth of online social networks over the last decade has raised the need to approach the data derived from them in a variety of ways in order to optimally analyze them and draw useful conclusions. From the advent of the initial centralized social networks, to the current trend of decentralized, the big data generated needs to be processed with mining and visualization methodologies so as to understand results that have a very big impact even at the overall social level, such as that of spreading fake news. In the present dissertation, the subject of study is initially the overview of the big data mining methodologies and visualization techniques. The study will focus on data generated by social networks in order to analyze the quality and quantity of results that can lead to a safe use of social networks. The appropriate way to visualize the data will be explored and designed, and its effectiveness in scenarios such as the dissemination of fake news will be evaluated.