Predictive Analytical Model for Microblogging Data Using Asset Bubble Modelling

2. Related Work

Social media platforms allow collecting data and analyzing different types of information from different users and on different topics. Examples of the social media platforms include Facebook, Google+, Twitter and others. Facebook and other social media platforms data need to be statically collected and analyzed whereas twitter provides a streaming API wherein the data can be gathered in real-time. Hence, in this paper the proposed method is used with microblog twitter. Many of the experiments related to sentimental analysis choose twitter as the source since it provides the streaming service for analysis (Owen et.al). However, there are certain drawbacks of the streaming service that include scalability and processing. In order to address this issue, the proposed system includes Apache kafka as the platform for receiving the messages from the twitter. Apache kafka includes a message queuing system wherein it can collect one million messages per second (Kreps et al., 2011).