ABSTRACT
Even though the amount of social media data is increasing explosively, we understand very little from them and only become saturated by reading each SNS timeline. In addition, each piece of data is too fragmented. For example, a tweet is a mere sequence of less than 140 words. We often obtain news updates or notices from one tweet without understanding the perspective of a focused issue. In the current method, most search or retrieval methods are done per data. For example, the current systems retrieve data that correspond to a user’s query to a bit of appropriate data and focus on each piece of data. We cannot understand an issue by just focusing on one bit of data. Current search or retrieval systems do not correspond to the current social media situation. Since there are many types of social media on the Web, we must realize a new analysis and visualization method that interconnects various massive heterogeneous social media contents.
