Detecting Emergent Conflicts through Web Mining and Visualization

An ocean of data is available on the web. From this ocean of data, information can in theory be extracted and used by analysts for detecting emergent trends (trend spotting). However, to do this manually is a daunting and nearly impossible task. We describe a semi-automatic system in which data is automatically collected from selected sources, and to which linguistic analysis is applied to extract e.g., entities and events. After combining the extracted information with human intelligence reports, the results are visualized to the user of the system who can interact with it in order to obtain a better awareness of historic as well as emergent trends. A prototype of the proposed system has been implemented and some initial results are presented in the paper.