Discovering spread mode of public opinions in incidents and mapping it with GIS: A case on big geospatial data analytics

In the Big Data era, microblog is being increasingly investigated due to its big data features. For example, it provides large volumes of data for discovery of knowledge about public opinion and physical environment. Once connected with their location information, this kind of Volunteered Geographic Information provides new opportunities for geographical analysis. User generated content submitted voluntarily through microblog can be gathered as a collection of opinions of many different people and mined. Public opinion monitoring has been widely used to monitor marketing in enterprises, and provides information for decision making in governments. This paper investigate the spread mode of public opinion in incidents with the help of microblog and find laws about the spread mode across physical spaces with combination of GIS and statistical method.