Tokyo Metropolitan University Research Center

首都大学東京 Tokyo Metropolitan University

Social Big Data

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Academic background

Constructing general theories and modeling frameworks on social big data to contribute to the further evolution of the big data field

Director of research center:Professor Hiroshi ISHIKAWA, Dr. Science

Director of research center:
Professor Hiroshi ISHIKAWA, Dr. Science
Department of Information and Communications Systems,
Graduate School of System Design

Big data, which is attracting attention as an important source of knowledge, includes data derived from social media (social data) and observational data derived from the real world (real world data). It is possible to discover new value by analyzing these interrelatedly, and the results of doing so can be used in important fields such as tourism and disaster prevention through applications like behavioral analysis and prediction of users, optimization of facilities and social infrastructure, and the improvement of convenience. These kinds of data and analysis activities are known collectively as social big data.

Social big data normally has all or some of spatial information, temporal information and semantic information. For example, social data can have explicit semantics (content and tags), but real world data only has potential semantics. On the other hand, temporal information exists in data and, in many cases, spatial information also exists in data due to the development of GPS. Social big data is useful, but in its present condition, there are also important issues in analysis and visualization.

At this Research Center, in order to construct general theories and modeling frameworks on social big data, our main themes are research and development on: [1] the foundations for the visualization of analysis of temporal and spatial information; [2] the scalable and robust natural language analysis technology required for information extraction from social data; [3] technology to discover the relationships between multiple data sources required for integrated analysis; and [4] parallel visualization technology including the collection and processing of social data.