Acknowledgement
This work was supported by a Korea Science and Engineering Foundation (KOSEF) grant funded by the Korea government (MOST) (NRF-2015R1A2A1A09007327).
Infrastructure development as national project suffers from social conflict which is one of main risk to be managed. Social conflicts have a negative impact on not only the social integration but also the national economy as they require enormous social costs to be solved. Against this backdrop, this study analyzes social conflict using articles published by online news media based on web-crawling and natural language processing (NLP) techniques. As an illustrative case, the Jeju Naval Base (JNB) project which is one of representative conflict case in South Korea is analyzed. Total of 21,788 articles and representative keywords are identified annually. Additionally, comparative analysis is conducted between the extracted keywords and actual events occurred during the project. The authors explain actual events in the JNB project based on the extracted words by the year. This study contributes to analyze social conflict and to extract meaningful information from unstructured data.
This work was supported by a Korea Science and Engineering Foundation (KOSEF) grant funded by the Korea government (MOST) (NRF-2015R1A2A1A09007327).