A New Big Data Architecture for Analysis: The Challenges on Social Media

Abstract

The streams of social media big data are now becoming an important issue. But the analytics method and tools for this data may not be able to find the useful information from this massive amount of data. The question then becomes: how do we create a high-performance platform and a method to efficiently analyse social networks’ big data; how to develop a suitable mining algorithm for finding useful information from social media big data. In this work, we propose a new hierarchical big data analysis for understanding human interaction, and we present a new method to measure the useful tweets of Twitter users based on the three factors of tweet texts. Finally, we use this test implementation score, in order to detect useful and classification tweets by interested degree.