Title
Detecting Emergent Conflicts through Web Mining and Visualization
Abstract
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.
Year
DOI
Venue
2011
10.1109/EISIC.2011.21
EISIC
Keywords
Field
DocType
web mining,initial result,human intelligence report,better awareness,emergent trend,semi-automatic system,proposed system,impossible task,selected source,linguistic analysis,detecting emergent conflicts,data visualisation,trend analysis,internet,data mining,media,pragmatics,computational linguistics,databases,computer science,data visualization
Data mining,Data visualization,Web mining,Pragmatics,Computer science,Human intelligence,Visualization,Computational linguistics,Spotting,The Internet
Conference
Citations 
PageRank 
References 
4
0.54
7
Authors
7
Name
Order
Citations
PageRank
Fredrik Johansson1957.18
Joel Brynielsson217320.20
Pontus Horling340.88
Michael Malm440.54
Christian Martenson5553.93
Staffan Truve640.54
Magnus Rosell7104.14