• The Journal of Bigdata
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• v.2 no.1
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• pp.27-39
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• 2017

The importance of online communication is getting increased by the rapid growth of smartphone supply and Social Network Service (SNS) use. Catching up with the trend, firms are actively use SNS to improve brand image, promote products, and communicate with customer. On the one hand, SNS is the channel for firms' marketing activities, but on the other, it is also the channel where the events related to the firms propagate in real time. Firms are led to unexpected state of crisis, when events are quickly spread out on SNS. Then firms are assessed their image by the way they deal with the state of crisis. This paper proposes to figure out user response on SNS according to each crisis response strategies by analyzing event-related twitter data when crisis situations of firms arise. We classify crisis response strategies into response attitude, defensive and accommodative response, and response speed, fast and slow response. This paper suggests optimal crisis response strategy to firms regarding state of crisis propagated on SNS.

• Journal of Internet Computing and Services
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• v.15 no.1
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• pp.125-134
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• 2014

As the social media which was simple communication media is activated on account of twitter and facebook, it's usability and importance are growing recently. Although many companies are making full use of its the capacity of information diffusion for marketing, the adverse effects of this capacity are growing. Because social network is formed and communicates based on friendships and relationships, the spreading speed of the spam and mal-ware is very swift. In this paper, we draw parameters affecting malicious data diffusion in social network environment, and compare and analyze the diffusion capacity of each parameters by propagation experiment with XSS Worm and Koobface Worm. In addition, we discuss the structural characteristics of social network environment and then proposed malicious data propagation model based on parameters affecting information diffusion. n this paper, we made up BA and HK models based on SI model, dynamic model, to conduct the experiments, and as a result of the experiments it was proved that parameters which effect on propagation of XSS Worm and Koobface Worm are clustering coefficient and closeness centrality.

• Journal of Cadastre & Land InformatiX
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• v.49 no.2
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• pp.67-82
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• 2019

The purpose of this study is to analyze the issues and perceptions of smart cities. First, based on the big data analysis platform, big data analysis on smart cities were conducted to derive keywords by year, word cloud, and frequency of generation of smart city keywords by time. Second, trend and flow by area were analyzed by reclassifying major keywords by year based on meta-keywords. Third, emotional recognition flow for smart cities and major emotional keywords were derived. While U-City in the past is mostly centered on creating infrastructure for new towns, recent smart cities are focusing on sustainable urban construction led by citizens, according to the analysis. In addition, it was analyzed that while infrastructure, service, and technology were emphasized in the past, management and methodology were emphasized recently, and positive perception of smart cities was growing. The study could be used as basic data for the past, present and future of smart cities in Korea at a time when smart city services are being built across the country.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.11
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• pp.47-54
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• 2015

The number of users of SNS such as Twitter and Facebook increases due to the development of internet and the spread of supply of mobile devices such as smart phone. Moreover, there are also an increasing number of content pollution problems that pollute SNS by posting a product advertisement, defamatory comment and adult contents, and so on. This paper proposes an improved method of extracting the feature of content polluter for detecting a content polluter in SNS. In particular, this paper presents a method of extracting the feature of content polluter on the basis of incremental approach that considers only increment in data, not batch processing system of entire data in order to efficiently extract the feature value of new user data at the stage of predicting and classifying a content polluter. And it comparatively assesses whether the proposed method maintains classification accuracy and improves time efficiency in comparison with batch processing method through experiment.

• The Journal of the Korea Contents Association
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• v.19 no.3
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• pp.1-9
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• 2019

The purposes of the study are to investigate Koreans' perception about Vietnam by analyzing social big data and to seek changing direction in perception. For the purposes, the texts about Vietnam in Naver Blog and Twitter and the number of search and click for Vietnam in Naver were analyzed by Social Metrics of Daum Soft and Datalab of Naver. The study also analyzed the annual change of their interest in Vietnam based on social media. The results showed that Koreans still remember the Vietnam war, have a positive emotion toward Vietnam, and view Vietnam as a country where we can gain mutual benefit by exchange. The findings also indicated that Koreans perceive Vietnam as a favorite tourist spot regardless of age. Meanwhile, children under 12 showed a different pattern of an annual change in perception. It might be a positive sign that Koreans' interest region toward Vietnam would be diversified because children under 12 would be the central axis of cultural contents.

• The Journal of Bigdata
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• v.7 no.2
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• pp.235-244
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• 2022

The rental history data of public bicycles in Seoul were analyzed to examine how pandemic phenomena such as COVID-19 caused changes in people's micro mobility. Data for 2019 and 2021 were compared and analyzed by dividing them before and after COVID-19. Data were collected from public data portal sites, and data marts were created for in-depth analysis. In order to compare the changes in the two periods, the riding direction type dimension and the rental station type dimension were added, and the derived variables (rotation rate per unit, riding speed) were newly created. There is no significant difference in the average rental time before and after COVID-19, but the average rental distance and average usage speed decreased. Even in the mobility of Ttareungi, you can see the slow rhythm of daily life. On weekdays, the usage rate was the highest during commuting hours even before COVID-19, but it increased rapidly after COVID-19. It can be interpreted that people who are concerned about infection prefer Ttareungi to village buses as a means of micro-mobility. The results of data mart-based visualization and analysis proposed in this study will be able to provide insight into public bicycle operation and policy development. In future studies, it is necessary to combine SNS data such as Twitter and Instagram with public bicycle rental history data. It is expected that the value of related research can be improved by examining the behavior of bike users in various places.

• Journal of the Korean Data and Information Science Society
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• v.26 no.5
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• pp.1087-1095
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• 2015

Influenza, commonly known as "the flu", is an infectious disease caused by the influenza virus. We consider, in this paper, regression models as a prediction model of influenza disease. While most of previous researches use mainly the meteorological variables as a predictive variables, we consider social media information in the models. As a result, we found that the contributions of two-type of informations are comparable. We used the medical treatment data of influenza provided by Natioal Health Insurance Survice (NHIS) and the meteorological data provided by Korea Meteorological Administration (KMA). We collect social media information (twitter buzz amount) from Twitter. Time series model is also considered for comparison.

• Journal of Information Technology Applications and Management
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• v.20 no.2
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• pp.109-125
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• 2013

As the number of SNS users is increasing, it has been very important how companies use SNS strategically. As a result, studies have been performed for the utilization of SNS. Most of the studies, however, focused on the overall characteristics of SNS and did not consider the characteristics of individual SNS. This study classified the main purpose of SNS use as relation-oriented purpose and information-oriented purpose, and identified the types of SNS from two viewpoints : service type and openness. Based on the classification, this study identified the characteristics of Cyworld, Facebook, and Twitter respectively, and analyzed the difference of the purpose of SNS users according to the characteristics of each service. The results showed that more users had the information-oriented purpose in the order of Twitter, Facebook, and Cyworld. There was no difference in the relation-oriented purpose among the three services. The analyses of the motive to join a group or a party made similar results. The results of additional analyses showed that the ratio of users with many acquaintances was high in the order of Facebook, Twitter, and Cyworld. In addition, more users checked their timeline or news feed more frequently in the order of Facebook, Twitter, and Cyworld.

• Fashion & Textile Research Journal
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• v.22 no.4
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• pp.481-494
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• 2020

This study examined consumer perceptions and consumer responses of Halal cosmetics and compared them with vegan cosmetics, which is a term similarly used. Twitter API of Python 3.7 was used to collect the keywords '#halalcosmetics' and '#vegancosmetics'. First, the main perception of consumers on Halal cosmetics focused on the original concept, image, expected efficacy, and factors to consider before purchase, religious keywords, labels and packaging for Halal cosmetics. Second, the main consumer perception of vegan cosmetics was the product concept, expected efficacy, factors to consider before purchase, related vegan industry, image, and vegan cosmetic components. Third, the consumer perceptions of Halal cosmetics and vegan cosmetics were similar in multiple ways, and both concepts included the Cruelty-free concept. Fourth, consumer satisfaction factors included cosmetics color, brand's consumer service, efficacy, smell, packaging design, reasonable price, effects, and formulation of cosmetics as well as satisfaction with Halal certification, and satisfaction of Vegan consumers. Consumer dissatisfaction factors included smell, flavor, delay in shipping, dissatisfaction with formulation, discrepancy between actual color and computer screen, concern and distrust about the use of prohibited ingredients for Halal products. This study examined consumer perceptions and reactions to Halal and vegan cosmetics to create basic knowledge for niche markets that are emerging as an ethical beauty consumption trend.

• Journal of IKEEE
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• v.20 no.3
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• pp.235-240
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• 2016

In this study, we use the data collected from Twitter, as an SNS(Social Networking Service), for service innovation. This data was collected and processed by Flume. The data set in May 2016 was 4,766 and 15,543 from company S and company X, respectively. We were able to figure out the emotional atmosphere of the two companies through the sentiment analysis(SA) and to find out about the vertical relationship through the bibliometric analysis(BA). Furthermore, we were able to grasp the horizontal relationship through the social network analysis(SNA). It was concluded that SNS was worth while to derive an innovative item.