• Journal of the Korea Fashion and Costume Design Association
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• v.18 no.3
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• pp.113-127
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• 2016

This study was aimed to analyzing the fashion style worn during the election campaign in the 16-18 Korea presidential candidates. In order to derive a comprehensive fashion style of each candidate it was classified as outfits, items, colors, patterns, accessories and the like. Research data was collected through literature, newspapers, Internet sites, etc., and SPSS statistical package was performed. In research data, 16 presidential candidates photographs were 87, 17 presidential candidates photographs were 82, 18 presidential candidates photographs were 155 as photograph by exposure to the media during each presidential campaign. The results of this study are as follows: In the fashion style of presidential candidates, male candidates mainly dressed in a tie and suit, but the 18 candidates dressed in casual wear unlike previous candidates. In tie color, 16 appeared in the red series, 17 election and 18 election appeared in blue series. Female candidate, Park Geun-hye candidate dressed in the combination of a jacket and blouse and pants. Therefore fashion style of presidential candidates got a strong symbolic image functions as political lines, ideologies, beliefs, and the campaign promises. Because describing the fashion style of candidates based on the statistical result, it requires attention to generalization.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.48 no.3
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• pp.18-26
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• 2011

Social network services whose users increase rapidly is the online services that reflect social network. They are used for various purposes such as strategy of election, commercial advertisement and marketing, educational information sharing and exchange of medical knowledge and opinions. These services make users form social networks with other users who have common interests and expand their relationships by releasing their personal information and utilizing other users' social networks. However, the social network services based on open and sharing of information raise various security threats such as violation of privacy and phishing. In this paper, we propose a group key management scheme and protocols using key rings to protect communication of small groups in social network services.

• Journal of Intelligence and Information Systems
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• v.24 no.3
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• pp.199-219
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• 2018

With the everyday use of the Internet and the spread of various smart devices, users have been able to communicate in real time and the existing communication style has changed. Due to the change of the information subject by the Internet, data became more massive and caused the very large information called big data. These Big Data are seen as a new opportunity to understand social issues. In particular, text mining explores patterns using unstructured text data to find meaningful information. Since text data exists in various places such as newspaper, book, and web, the amount of data is very diverse and large, so it is suitable for understanding social reality. In recent years, there has been an increasing number of attempts to analyze texts from web such as SNS and blogs where the public can communicate freely. It is recognized as a useful method to grasp public opinion immediately so it can be used for political, social and cultural issue research. Text mining has received much attention in order to investigate the public's reputation for candidates, and to predict the voting rate instead of the polling. This is because many people question the credibility of the survey. Also, People tend to refuse or reveal their real intention when they are asked to respond to the poll. This study collected comments from the largest Internet portal site in Korea and conducted research on the 19th Korean presidential election in 2017. We collected 226,447 comments from April 29, 2017 to May 7, 2017, which includes the prohibition period of public opinion polls just prior to the presidential election day. We analyzed frequencies, associative emotional words, topic emotions, and candidate voting rates. By frequency analysis, we identified the words that are the most important issues per day. Particularly, according to the result of the presidential debate, it was seen that the candidate who became an issue was located at the top of the frequency analysis. By the analysis of associative emotional words, we were able to identify issues most relevant to each candidate. The topic emotion analysis was used to identify each candidate's topic and to express the emotions of the public on the topics. Finally, we estimated the voting rate by combining the volume of comments and sentiment score. By doing above, we explored the issues for each candidate and predicted the voting rate. The analysis showed that news comments is an effective tool for tracking the issue of presidential candidates and for predicting the voting rate. Particularly, this study showed issues per day and quantitative index for sentiment. Also it predicted voting rate for each candidate and precisely matched the ranking of the top five candidates. Each candidate will be able to objectively grasp public opinion and reflect it to the election strategy. Candidates can use positive issues more actively on election strategies, and try to correct negative issues. Particularly, candidates should be aware that they can get severe damage to their reputation if they face a moral problem. Voters can objectively look at issues and public opinion about each candidate and make more informed decisions when voting. If they refer to the results of this study before voting, they will be able to see the opinions of the public from the Big Data, and vote for a candidate with a more objective perspective. If the candidates have a campaign with reference to Big Data Analysis, the public will be more active on the web, recognizing that their wants are being reflected. The way of expressing their political views can be done in various web places. This can contribute to the act of political participation by the people.