• The Journal of Society for e-Business Studies
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• v.24 no.3
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• pp.163-182
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• 2019

Analyzing the frequency and correlation of the news keywords in the modern society that are becoming complicated according to the time flow is a very important research to discuss the response and solution to issues. This paper analyzed the relationship between the flow of social keyword and major issues through the analysis of news big data for 10 years (2009~2018). In this study, political issues, education and social culture, gender conflicts and social problems were presented as major issues. And, to study the change and flow of issues, it analyzed the change of the issue by dividing it into five years. Through this, the changes and countermeasures of social issues were studied. As a result, the keywords (economy, police) that are closely related to the people's life were analyzed as keywords that are very important in our society regardless of the flow of time. In addition, keyword such as 'safety' have decreased in increasing rate compared to frequency in recent years. Through this, it can be inferred that it is necessary to improve the awareness of safety in our society.

• KIPS Transactions on Software and Data Engineering
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• v.8 no.1
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• pp.13-18
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• 2019

In this study, we investigate important keywords and their relationships among the keywords for social issues, and analyze topics to find subjects of the social issues. In particular, we collected twitter data with the keyword 'metoo' which has attracted much attention in these days, and perform keyword analysis and topic modeling. First, we preprocess the twitter data, identified important keywords, and analyzed the relatedness of the keywords. After then, topic modeling is performed to find subjects related to 'metoo'. Our experimental results showed that relatedness of keywords and subjects on social issues in twitter are well identified based on keyword analysis and topic modeling.

• Korean journal of communication and information
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• v.26
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• pp.157-208
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• 2004

This study explored how television news constructed an issue of the building of a nuclear waste facility on Wido, an issue which displayed a social conflict in the latter half of the year 2003. To do this, this study conducted frame analysis on KBS and MBC main news including national and local ones, broadcasted from 11 July, 2003 to 10 December, 2003. It was found that television news tended to stress violent protests against site designation and social disorder rather than the causes of a conflict and its solutions. Therefore, news reporting excluded fundamental reasons of conflict such as the governmental decision-making process of site designation, geological suitability, safety issue and nuclear energy policy, emphasizing the confrontation and clash between pro and con groups of site designation. This indicates that television news defines an issue of the building of a nuclear waste facility as the local conflict between groups, the police and demonstrators, or neighbors who approve and protest the site designation, not as the national issue of nuclear policy.

• Proceedings of the Korean Society of Computer Information Conference
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• 2020.07a
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• pp.307-310
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• 2020

본 논문에서 이슈 키워드 추출을 위해 텍스트 마이닝(Text Mining) 기술을 요구한다. 사회적 이슈 키워드를 추출하기 위해 키워드 수집 모델이 되는 사이트에서 크롤링(crawling)을 수행한 뒤, 형태소 단위 의미있는 단어를 수집하기 위해 형태소 분석(morphological analysis)을 수행한다. 한국어 형태소 분석을 위해 파이썬의 코엔엘파이(KoNLPy) 패키지를 활용한다. 형태소 분석을 통해 나뉘어진 단어에서 통계를 내어 이슈 키워드 추출한다. 이슈 키워드를 뒷받침할 연관 단어를 분석하기 위해 단어 임베딩(Word Embedding)을 수행한다. 단어 임베딩 수행을 위해 Word2Vec 모델 중 Skip-Gram 방법론을 적용하여 연관 단어를 분석하도록 개발하였다. 웹 소켓(Web Socket) 통신을 통한 채팅 프로그램의 상단에 분석한 이슈 키워드와 연관 단어를 출력하도록 개발하였다.

• Journal of Digital Convergence
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• v.17 no.4
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• pp.279-284
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• 2019

The purpose of this study is to investigate the direction of communication design through in-depth interviews on the topic of gender equality, which is an active theme of social issue happening worldwide, and to suggest a direction to provide better social issue communication direction. In order to do so, firstly, I researched case studies and investigated the characteristics of gender magazines such as If, Ferm and Womankind. Secondly, I conducted an empirical study of in-depth interviews to identify the emotional adjectives by women and men by different age groups from gender equality storytelling magazine experience. As a result, I was able to grasp two points necessary. First of all, for the gender equality content messages closely related to everyday stories level down the barrier and become easier to empathize with. Second of all, the more complex the social issues are, the more sustainable and credible if the content developed steadily and contingently. This study is meaningful in that it suggested a series of directions for communicating gender equality issues. Future research should complement the suggested directions for gender equality communication design and contribute to guiding further directions.

• Journal of Digital Convergence
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• v.19 no.3
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• pp.167-176
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• 2021

With development of big data analysis technology, many studies to find social issues using texts mining techniques have been conducted. In order to derive social issues, previous studies performed in a way that collects a large amount of text data from news or SNS, and then analyzes issues based on text mining techniques such as topic modeling and terms network analysis. Social issues are the results of various social phenomena and factors. However, since previous studies focused on deriving social issues that are results of various causes, there are limitations to revealing the cause of the issues. In order to effectively respond to social issues, it is necessary not only to derive social issues, but also to be able to identify the causes of social issues. In this study, in order to overcome these limitations, we proposed a method of deriving the factors that cause social issues from texts related to social issues based on the theory of part of Korean linguistics. To do this, we collected news data related to social issues for three years from 2017 to 2019 and proposed a methodology to find causes based causal sentences based on text mining techniques.

• Journal of Convergence for Information Technology
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• v.9 no.11
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• pp.81-91
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• 2019

Recently, social network service (SNS) is actively used by public. Among them, Twitter has a lot of tweets including sentiment and it is convenient to collect data through open Aplication Programming Interface (API). In this paper, we analyze social issues and suggest the possibility of using them in marketing through sentimental information of users. In this paper, we collect twitter text about social issues and classify as positive or negative by sentiment classifier to provide qualitative analysis. We provide a quantitative analysis by analyzing the correlation between the number of like and retweet of each tweet. As a result of the qualitative analysis, we suggest solutions to attract the interest of the public or consumers. As a result of the quantitative analysis, we conclude that the positive tweet should be brief to attract the users' attention on the Twitter. As future work, we will continue to analyze various social issues.

• Journal of the Korean Data and Information Science Society
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• v.26 no.5
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• pp.1167-1173
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• 2015

The development of information and communication technology like SNS, blogs, and bulletin boards, was provided a variety of places where you can express your thoughts and comments and allowing Big Data to grow, many people reveal the opinion of the social issues in SNS such as Twitter. In this study, we would like to pre-built sentimental dictionary about social issues and conduct a sentimental analysis with structured dictionary, to gather opinions on social issues that are created on twitter. The data that I used is "bikini", "nakkomsu" including tweet. As the result of analysis, precision is 61% and F1- score is 74%. This study expect to suggest the standard of dictionary construction allowing you to classify positive/negative opinion on specific social issues.

• 월간 기계설비
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• s.256
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• pp.58-59
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• 2011

• Korean Journal of Legislative Studies
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• v.17 no.3
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• pp.5-28
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• 2011

이 논문은 선진민주주의 국가의 선거경쟁에서 제시되는 정당 매니페스토 자료와 사회정책 자료를 사용하여 국가별 정당 간 입장의 차이, 정부당파성과 복지국가의 관계, 그리고 복지국가 이슈에 관한 정당양극화의 문제에 대해 경험적 분석을 제시한다. 이 논문의 분석이 제시하는 바는 다음과 같다. 첫째, 선진민주주의 국가의 주요 좌우파 정당 간 사회정책 입장의 차이는 국가별로 편차를 보인다. 복지국가 이슈와 관련한 정당양극화의 정도는 기존 복지국가 체계의 특성, 선거제도, 또는 선거경쟁에서 나타나는 복지국가 이슈의 유형에 따라 다른 것으로 보인다. 둘째, 집권정당의 당파성이 복지국가에 미치는 영향을 확인할 수 있다. 셋째, 정당이 복지국가에 미치는 영향이 제한적이거나 혹은 제도적 맥락에 조건지어진다는 점을 고려할 필요가 있다. 어쩌면 정당 및 정부당파성이 복지국가에 미치는 영향은 협의제 민주주의(consensus democracies) 유형의 국가들보다는 다수제 민주주의(majoritarian democracies) 유형의 국가들에서 더 뚜렷하게 나타나는 것인지도 모른다. 넷째, 정당의 정책입장의 변화는 경쟁하는 주요정당의 정책변화에 영향을 받기도 한다. 또한 이슈유형에 따라 위치이슈와 합의이슈로 구분할 수 있는데, 각 국가별 선거경쟁과 복지국가 논의는 다양한 형태를 가지면서 진행된다.