• Journal of the Society of Disaster Information
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• v.13 no.1
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• pp.89-95
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• 2017

The cases of animals unusual behavior have been reported occasionally before a major disaster occurs. Could animals unusual behavior associated with a major disaster occurrence, if so, could we foreknow a disaster occurrence? The purpose of study is to quest an answer through literature reviews on the relation between animals unusual behavior and premonitory symptoms of an earthquake. These empirical studies are classified three parts according as methodological framework; statistical analysis, experimental analysis, observation analysis. The results are simply divided as two, 'animals unusual behavior may be seen as a precursor of pre-disaster phenomena' and 'difficult to see.' A number of studies have been performed abroad, however there is no one in Korea. Most of the studies point out common limitations-difficult to verify the reliability of data, accidentally get and fewer samples of data, difficulty of ensuring appropriate data, etc. That is why more related research with animals unusual behavior and disaster occurrence is needed to validate cause-and-effect relation of animal unusual behavior and pre-disaster phenomena.

• Journal of Korea Multimedia Society
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• v.16 no.6
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• pp.667-677
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• 2013

With the huge success of Social Network Services, studies on social network analysis to extract the current issues or to track the symptoms of epidemic disease are being carried out actively. On Twitter, tweets reflect people's reaction to an event and users' individual status well, so it is possible to detect an event regarding a tweet as a sensory value. Recently, social signals are used to detect the spread of illness like the flu as well as the occurrence of disaster event like an earthquake in early stages. In this paper, we set up a cold as a target event and regarded tweets as Cold Signals. To evaluate the reliability of Cold Signals, we analyzed correlations between weather factors and the cold index provided by Korea Meteorological Administration.