• Title/Summary/Keyword: Earthquake Measures

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A Study on the Differences of Information Diffusion Based on the Type of Media and Information (매체와 정보유형에 따른 정보확산 차이에 대한 연구)

  • Lee, Sang-Gun;Kim, Jin-Hwa;Baek, Heon;Lee, Eui-Bang
    • Journal of Intelligence and Information Systems
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    • v.19 no.4
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    • pp.133-146
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    • 2013
  • While the use of internet is routine nowadays, users receive and share information through a variety of media. Through the use of internet, information delivery media is diversifying from traditional media of one-way communication, such as newspaper, TV, and radio, into media of two-way communication. In contrast of traditional media, blogs enable individuals to directly upload and share news, which can be considered to have a differential speed of information diffusion than news media that convey information unilaterally. Therefore this Study focused on the difference between online news and social media blogs. Moreover, there are variations in the speed of information diffusion because that information closely related to one person boosts communications between individuals. We believe that users' standard of evaluation would change based on the types of information. As well, the speed of information diffusion would change based on the level of proximity. Therefore, the purpose of this study is to examine the differences in information diffusion based on the types of media. And then information is segmentalized and an examination is done to see how information diffusion differentiates based on the types of information. This study used the Bass diffusion model, which has been frequently used because this model has higher explanatory power than other models by explaining diffusion of market through innovation effect and imitation effect. Also this model has been applied a lot in other information diffusion related studies. The Bass diffusion model includes an innovation effect and an imitation effect. Innovation effect measures the early-stage impact, while the imitation effect measures the impact of word of mouth at the later stage. According to Mahajan et al. (2000), Innovation effect is emphasized by usefulness and ease-of-use, as well Imitation effect is emphasized by subjective norm and word-of-mouth. Also, according to Lee et al. (2011), Innovation effect is emphasized by mass communication. According to Moore and Benbasat (1996), Innovation effect is emphasized by relative advantage. Because Imitation effect is adopted by within-group influences and Innovation effects is adopted by product's or service's innovation. Therefore, ours study compared online news and social media blogs to examine the differences between media. We also choose different types of information including entertainment related information "Psy Gentelman", Current affair news "Earthquake in Sichuan, China", and product related information "Galaxy S4" in order to examine the variations on information diffusion. We considered that users' information proximity alters based on the types of information. Hence, we chose the three types of information mentioned above, which have different level of proximity from users' standpoint, in order to examine the flow of information diffusion. The first conclusion of this study is that different media has similar effect on information diffusion, even the types of media of information provider are different. Information diffusion has only been distinguished by a disparity between proximity of information. Second, information diffusions differ based on types of information. From the standpoint of users, product and entertainment related information has high imitation effect because of word of mouth. On the other hand, imitation effect dominates innovation effect on Current affair news. From the results of this study, the flow changes of information diffusion is examined and be applied to practical use. This study has some limitations, and those limitations would be able to provide opportunities and suggestions for future research. Presenting the difference of Information diffusion according to media and proximity has difficulties for generalization of theory due to small sample size. Therefore, if further studies adopt to a request for an increase of sample size and media diversity, difference of the information diffusion according to media type and information proximity could be understood more detailed.

Relationship Analysis between Lineaments and Epicenters using Hotspot Analysis: The Case of Geochang Region, South Korea (핫스팟 분석을 통한 거창지역의 선구조선과 진앙의 상관관계 분석)

  • Jo, Hyun-Woo;Chi, Kwang-Hoon;Cha, Sungeun;Kim, Eunji;Lee, Woo-Kyun
    • Korean Journal of Remote Sensing
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    • v.33 no.5_1
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    • pp.469-480
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    • 2017
  • This study aims to understand the relationship between lineaments and epicenters in Geochang region, Gyungsangnam-do, South Korea. An instrumental observation of earthquakes has been started by Korea Meteorological Administration (KMA) since 1978 and there were 6 earthquakes with magnitude ranging 2 to 2.5 in Geochang region from 1978 to 2016. Lineaments were extracted from LANDSAT 8 satellite image and shaded relief map displayed in 3-dimension using Digital Elevation Model (DEM). Then, lineament density was statistically examined by hotspot analysis. Hexagonal grids were generated to perform the analysis because hexagonal pattern expresses lineaments with less discontinuity than square girds, and the size of the grid was selected to minimize a variance of lineament density. Since hotspot analysis measures the extent of clustering with Z score, Z scores computed with lineaments' frequency ($L_f$), length ($L_d$), and intersection ($L_t$) were used to find lineament clusters in the density map. Furthermore, the Z scores were extracted from the epicenters and examined to see the relevance of each density elements to epicenters. As a result, 15 among 18 densities,recorded as 3 elements in 6 epicenters, were higher than 1.65 which is 95% of the standard normal distribution. This indicates that epicenters coincide with high density area. Especially, $L_f$ and $L_t$ had a significant relationship with epicenter, being located in upper 95% of the standard normal distribution, except for one epicenter in $L_t$. This study can be used to identify potential seismic zones by improving the accuracy of expressing lineaments' spatial distribution and analyzing relationship between lineament density and epicenter. However, additional studies in wider study area with more epicenters are recommended to promote the results.