• KIPS Transactions on Software and Data Engineering
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• 제7권6호
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• pp.229-238
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• 2018

The rapid response of disaster accidents can be archived through the organical involvement of various disaster and safety control agencies. To define the terminology of disaster safety is essential for communication between disaster safety agencies and well as announcement for the public. Also, to efficiently construct a word dictionary of disaster safety terminology, it's necessary to define the priority of the terms. In order to establish direction of word dictionary construction, this paper compares the usage of disaster safety terminology by media: word dictionary, new media, and social media, respectively. Based on the terminology resources collected from each media, we visualized the distribution of terminology according to frequency weights and analyzed co-occurrence patterns. We also classified the types of terminology into four categories and proposed the priority in the construction of disaster safety word dictionary.

• Journal of the Korean Data and Information Science Society
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• 제27권4호
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• pp.845-854
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• 2016

Sentiment analysis or opinion mining is a technique of text mining employed to identify subjective information or opinions of an individual from documents in blogs, reviews, articles, or social networks. In the literature, only a problem of binary classification of ratings based on review texts in an online review. However, because there can be positive or negative reviews as well as neutral reviews, a multi-class classification will be more appropriate than the binary classification. To this end, we consider the multi-class classification of ratings based on review texts. In the preprocessing stage, we extract words related with ratings using chi-square statistic. Then the extracted words are used as input variables to multi-class classifiers such as support vector machines and proportional odds model to compare their predictive performances.

• Journal of the HCI Society of Korea
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• 제4권1호
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• pp.11-15
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• 2009

Social Network Service has been extremely popular these days and providing diverse features and functions to users. Social networking and interest sharing in between users are key factors of SNS and this circles back to draw more users to the service. Web is the first media to provide SNS and mobile is the next. The service based on mobile environmental uniqueness such as Location-based-service(LBS) is the key success factors to convert users to web SNS to mobile SNS. TV has also been a possible SSN market to draw users to share interests and participation. However TV has been always community electronics in family members and personalization to provide SNS has been barrier to overcome. In this study, we explorer ideas of key factors of personalization in TV environment and conducted a field study to define characteristics of TV personalization in terms of depth, method, style and structure. Research finds out that there are significant differences in these categories.

• Convergence Security Journal
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• 제13권1호
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• pp.37-43
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• 2013

In 2010, the Ministry of National Defense decided to build a MegaCenter including the cloud computing technology by 2014, as part of the '2012 Information Service Plan', which is now underway. The Cloud computing system environment should be designed applying cloud computing technology and policy for an efficient infrastructure that many IT resources are available in the data center as a concentrated form. That is, the system should be designed in such a way that clouding services will be efficiently provided to meet the needs of users and there will not be unnecessary waste of resources. However, in order to build an optimal system, it should be possible to predict the service performance and the resource availability at the initial phase of system design. In this paper, using the CloudAnalyst simulator to predict availability of the K-defence cloud computing system service, conducts cloud modeling and analysis of the 'Facebook', one of the most famous social network service applications with most users in the world. An Optimal K-Defense cloud computing design model is proposed through simulation results.

• The Journal of Information Systems
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• 제29권2호
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• pp.221-242
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• 2020

Purpose This study collects data of the recently activated online black market and analyzes it to present a specific method for preparing for a hacking attack. This study aims to make safe from the cyber attacks, including hacking, from the perspective of individuals and businesses by closely analyzing hacking methods and tools in a situation where they are easily shared. Design/methodology/approach To prepare for the hacking attack through the online black market, this study uses the routine activity theory to identify the opportunity factors of the hacking attack. Based on this, text mining and social network techniques are applied to reveal the most dangerous areas of security. It finds out suitable targets in routine activity theory through text mining techniques and motivated offenders through social network analysis. Lastly, the absence of guardians and the parts required by guardians are extracted using both analysis techniques simultaneously. Findings As a result of text mining, there was a large supply of hacking gift cards, and the demand to attack sites such as Amazon and Netflix was very high. In addition, interest in accounts and combos was in high demand and supply. As a result of social network analysis, users who actively share hacking information and tools can be identified. When these two analyzes were synthesized, it was found that specialized managers are required in the areas of proxy, maker and many managers are required for the buyer network, and skilled managers are required for the seller network.

• Journal of Convergence for Information Technology
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• 제11권10호
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• pp.1-9
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• 2021

Although interest in the metaverse increases due to the pandemic, the understanding of the metaverse interest factor, which is an essential element for the sustainability of any metaverse platform, is lacking. This study aims to reveal the interest factors of metaverse services by analyzing user community discourse. We collected user community discourses from and applied LDA to extract topics. Further, we categorize the factors into growth and verifiable indicators, various levels of interaction, self-expression and freedom, and connection with the real world. The content planning direction of the game-based metaverse of utilization was derived. This study is meaningful in that it analyzes the interest factors of the metaverse based on the empirical evidence of user discourse data.

• Journal of the Korea Society of Computer and Information
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• 제26권4호
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• pp.231-237
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• 2021

Over a decade ago, Krasnova et al. identified the factors that influence Facebook users' self-disclosure. These factors include perceived risks, relationship building, relationship maintenance, self-presentation, and enjoyment. Meanwhile, during the past 10 years, there have been significant changes in terms of function, media, and competition. SNSs have been functionally enhanced, used in mobile environment, and had many competitors. Based on these facts, it is believed that the influence of the factors on self-disclosure is different from those of Krasnova et al. The purpose of this study is to verify through a replication study whether the factors adopted in the study of Krasnova et al. are still important in explaining self-exposure. The study empirically find the result significantly different from those of Krasnova et al. Based on the result, the study provides meaningful implications and suggestions for future research.

• The Journal of the Korea Contents Association
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• 제21권5호
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• pp.105-117
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• 2021

This study examined the factors that influence the emotional expression in comments on the hot news about the 'Restaurant Collapse in Linfen City, Shanxi Province' published in Sina Weibo.. As a result of the study, first, there were differences in emotional expression according to gender. Women expressed stronger anger, disappointment, sadness, and condemnation than men. Second, the intensity of emotional expression of users in the eastern region was significantly higher than that of users in the central and western region. Third, the greater the number of Weibo, the total number of blogs where users participated in comments and posted emotional expressions, the stronger the emotional expression was. Fourth, unauthenticated users showed stronger emotional expressions of disappointment and sadness than authenticated users. The results of this study present implications for the factors influencing emotional expression on hot news. This study is meaningful in that it can be compared with social networks such as Twitter and Facebook in the West by looking at the factors that influence emotional expression in the process of online public opinion formation in China, and also meaningful in that a big data analysis method was used in online news analysis.

• KIPS Transactions on Computer and Communication Systems
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• 제6권2호
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• pp.95-104
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• 2017

As the technology in smart device is growing and Social Network Services(SNS) are becoming more common, the data which is difficult to be processed by existing RDBMS are increasing. As a result of this, NoSQL databases are getting popular as an alternative for processing massive and unstructured data generated in real time. The demand for the technique of digital investigation of NoSQL databases is increasing as the businesses introducing NoSQL database in their system are increasing, although the technique of digital investigation of databases has been researched centered on RDMBS. New techniques of digital forensic investigation are needed as NoSQL Database has no schema to normalize and the storage method differs depending on the type of database and operation environment. Research on document-based database of NoSQL has been done but it is not applicable as itself to other types of NoSQL Database. Therefore, the way of operation and data model, grasp of operation environment, collection and analysis of artifacts and recovery technique of deleted data in HBase which is a NoSQL column-based database are presented in this paper. Also the proposed technique of digital forensic investigation to HBase is verified by an experimental scenario.

• KIPS Transactions on Software and Data Engineering
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• 제7권5호
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• pp.177-188
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• 2018

The scale of graph data has been increased rapidly because of the growth of mobile Internet applications and the proliferation of social network services. This brings upon the imminent necessity of efficient distributed and parallel graph processing approach since the size of these large-scale graphs are easily over a capacity of a single machine. Currently, there are two popular parallel graph processing approaches, vertex-centric graph processing and block centric processing. While a vertex-centric graph processing approach can easily be applied to the parallel processing system, a block-centric graph processing approach is proposed to compensate the drawbacks of the vertex-centric approach. In these systems, the initial quality of graph partition affects to the overall performance significantly. However, it is a very difficult problem to divide the graph into optimal states at the initial phase. Thus, several dynamic load balancing techniques have been studied that suggest the progressive partitioning during the graph processing time. In this paper, we present a load balancing algorithms for the block-centric graph processing approach where most of dynamic load balancing techniques are focused on vertex-centric systems. Our proposed algorithm focus on an improvement of the graph partition quality by dynamically reassigning blocks in runtime, and suggests block split strategy for escaping local optimum solution.