• Journal of Nutrition and Health
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• v.36 no.5
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• pp.508-514
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• 2003

The purpose of this study was to analyze information about food and nutrition presented through the television broadcast media, with the aim of finding out the optimal communication method for supplying the general public with accurate information. To perform this study, a total of sixteen monitoring people were recruited and trained before and during the study. Five domestic TV channels were selected to be monitored, and the total monitoring period was six months. For maximum efficiency, the monitoring people were assigned to 8 teams. The results of the present study can be summarized as follows : First, the total reported cases of information about food and nutrition were 237, of which about 30% were judged appropriate and 70％ as inappropriate. Second, classifying each case by program type, information programs made up the highest portion at 82 cases (34.6%), cooking programs accounted for 76 cases (32.1%), news programs for 40 cases (16.9%), and entertainment programs for 7 cases (3.0%). The analysis showed that the greatest amount of incorrect information was found in dramas, followed by entertainment, information, cooking and news programs. Third, classifying each case by theme of contents monitored, meal preparation and cookery made up the highest portion at 86 cases (36.3%), foods accounted for 67 cases (28.3%), disease and diet-therapy for 40 cases (16.9%), eating habits for 31 cases (13.1%), and diet and fitness for 13 cases (5.5%). Incorrect information was conveyed most often on the themes of food habits, foods, disease and diet-therapy, cookery, and diet and fitness. Fourth, classifying each case by channel, Cable TV had the highest frequency at 72 cases (30.4%), MBC had 51 cases (21.5%), SBS had 43 cases (18.1%), KBS1 had 41 cases (17.3%) and KBS2 had 30 cases (12.7%). In conclusion, systematic monitoring should be continued to reduce the frequency of incorrect information being broadcast and to help ensure that accurate information is conveyed to the general public. Moreover, there should be a system of cooperation to provide information to help broadcast production teams establish a strategic program. Finally, it is essential to organize an advisory team by promoting links between the mass media and specialists in the field, and to develop an educational program on nutrition to help ensure the communication of accurate information on food and nutrition. (Korean J Nutrition 36(5): 508∼514, 2003)

• Journal of Broadcast Engineering
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• v.23 no.4
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• pp.536-548
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• 2018

Public data has been transformed from provider-oriented information disclosure to a form of personalized information sharing centered on individual citizens since government 3.0. As a result, the government is implementing policies and projects to maximize the value of public data and increase reuse. This study analyzes the issues related to public data in the news and seeks the status of government agencies and government projects by issue. We conducted semantic analysis on domestic online news and public agency bidding information including public data and conducted the work of linking major key words derived with social and economic values inherent in public data. As a result, major issues related to public data were divided into broader access to public data, growth of new technology, cooperation and conflict among stakeholders, and utilization of the private sector, which were closely related to transparency, efficiency, participation, and innovation mechanisms. Also major agencies of four issues include the Ministry of Strategy and Finance and Seoul, Ministry of Culture, Sports and Tourism and Gyeonggi-do, Ministry of Trade, Industry and Energy and Incheon, and Ministry of Land, Infrastructure and Transport and Gyeongsangbuk-do. Most of the issues are being led by the government.

• The Journal of the Korea Contents Association
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• v.20 no.9
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• pp.169-186
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• 2020

This study aims to examine the characteristics of news content and users' reactions in local broadcasting Youtube news' channel, and explore how the local media should response in the new online video environment. YouTube Open API sampled 3,950 news-related videos uploaded over a month on 31 YouTube news channels nationwide. The content analysis was performed on the basis of the analysis of individual videos, such as characteristics of each content and users' reactions. As a result, a few news channels have produced digital-only content, but the ratio has been very low, most were broadcast replay videos with titles and formats uploaded as they were. In some cases, it still operates as a comprehensive channel, which failed to show its expertise as an independent digital news platform. This shows that theses YouTube channels lacks differentiation from TV or its own web page, and is still skewed to the auxiliary role or online archive function of TV platform. Nevertheless, digital-only content, which can be a national issue based on regional expertise, has led to a higher number of views and users reactions, suggesting that is a realistic and effective strategy with expandability in online space in the future.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.3
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• pp.357-362
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• 2004

Language models are essential in predicting the next word in a spoken sentence, thereby enhancing the speech recognition accuracy, among other things. However, spoken language domains are too numerous, and therefore developers suffer from the lack of corpora with sufficient sizes. This paper proposes a method of combining two n-gram language models, one constructed from a very small corpus of the right domain of interest, the other constructed from a large but less adequate corpus, resulting in a significantly enhanced language model. This method is based on the observation that a small corpus from the right domain has high quality n-grams but has serious sparseness problem, while a large corpus from a different domain has more n-gram statistics but incorrectly biased. With our approach, two n-gram statistics are combined by extending the idea of Katz's backoff and therefore is called a dual-source backoff. We ran experiments with 3-gram language models constructed from newspaper corpora of several million to tens of million words together with models from smaller broadcast news corpora. The target domain was broadcast news. We obtained significant improvement (30%) by incorporating a small corpus around one thirtieth size of the newspaper corpus.

• Journal of Broadcast Engineering
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• v.7 no.1
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• pp.21-27
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• 2002

This paper presents a mews event reenactment system (NERS), which generates virtual character animations in a quick and convenient manner. Thus, NERS can be used to produce computer graphics(CG) scenes of news events that are hard to photograph, such as fire, traffic accident, cases of murder, and so on. By using plenty of captured motion data and CG model data this system produces an appropriate animation of virtual characters straightforwardly without any motion capturing device and actors in the authoring stage. NERS is designed to be capable of making virtual characters move along user-defined paths, stitching motions smoothly and modifyingthe positions and of the articulations of a virtual character in a specific frame. Therefore a virtual character can be controlled precisely so as to interact with the virtual environments and other characters. NERS provides both an interactive and script-based (MEL: Maya Embedded Language) interface so that user can this system in a convenient way. This system has been implemented as a plug-in of commercial CG tool, Maya (Alias/wavefront), in order to make use of its advanced functions

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2016.11a
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• pp.190-193
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• 2016

본 연구는 사행산업의 분야인 복권, 체육진흥투표권, 경마, 카지노에 대해 언론에서는 어떻게 다루어지고 있는지를 1990년부터 2015년까지의 뉴스데이터를 빅데이터 분석 방법 중 테스트의 의미연결망 분석을 통해 밝혀보고자 하는 연구이다. 이 논문은 의미망 분석을 통해 기사의 빈도와 연결성을 프레이밍과 시민관심 정도로 재조명 하여 기사에 대한 언론보도자의 의도와 시민의 인식차이를 밝혔고, 이를 통해 정책적 특성과 개혁과제를 탐색하였다. 분석결과 복권의 경우 당첨번호, 당첨금, 조작의혹 등 당첨에 대한 부분이 주제인 '사회문제' 형태였으며, 체육진흥투표권의 경우에는 사업입찰, 불법사이트, 발매대상 등 주로 사업추진과 불법사이트에 대한 '의무정보' 종류였고, 경마의 경우 사업장, 홍보, 기사 등으로 사업홍보나 광고 관련 뉴스이었고, 마지막으로 카지노의 경우에는 불법, 도박장, 외국인 등 '주요정보'에 해당하는 논문이었다. 시대에 따라 1990년대에는 카지노, 2000년대에는 복권, 2010년대에는 경마에 대한 기사보도가 많아졌으며, 이에 대한 시민의 반응도 사업비리, 당첨, 시민운동 등의 차이가 있었다. 마지막으로 기사의 빈도와 연결성이 나타내는 프레이밍 정도와 시민의 관심은 '1. 홍보광고, 2. 의무정보, 3. 사회이슈, 4. 주요정보' 네 가지로 구분되었으며 이 중 사고, 비리 등 주요기사로 구분되는 사회문제가 주요 공공의제로 형성되는 것을 확인할 수 있었다.

• Journal of Broadcast Engineering
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• v.26 no.5
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• pp.583-591
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• 2021

This paper explores variables that influence the prediction of OTT service experience and free(AVOD)/ paid(SVOD) service use. Research results showed that five variables such as gender, age, personal income, household composition, and e-commerce use experience had a significant impact on identifying OTT service experience and whether to use free or paid services. Also, it was found that the probability of using SVOD increases as they prefer news and drama genres and use OTT services for more time. In summary, those who are relatively young, have a high personal income, and are more adapted to digital environments such as e-commerce are more likely to use SVOD.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2020.07a
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• pp.619-623
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• 2020

한국어는 교착어로 1개 이상의 형태소가 단어를 이루고 있기 때문에 텍스트 분석 시 형태소를 분리하는 작업이 필요하다. 자연어를 처리하는 대부분의 알고리즘은 영미권에서 만들어졌고 영어는 굴절어로 특정 경우를 제외하고 일반적으로 하나의 형태소가 단어를 구성하는 구조이다. 그리고 영문은 주로 띄어쓰기 위주로 토큰화가 진행되기 때문에 텍스트 분석이 한국어에 비해 복잡함이 떨어지는 편이다. 이러한 이유들로 인해 한국어 텍스트 분석은 영문 텍스트 분석에 비해 한계점이 있다고 알려져 있다. 한국어 텍스트 분석의 성능 향상을 위해 본 논문에서는 번역 전처리 기법을 제안한다. 번역 전처리 기법이란 원본인 한국어 텍스트를 영문으로 번역하고 전처리를 거친 뒤 분석된 결과를 재번역하는 것이다. 본 논문에서는 한국어 뉴스 기사 데이터와 번역 전처리 기법이 적용된 영문 뉴스 텍스트 데이터를 사용했다. 그리고 주제어 역할을 하는 키워드를 단어 간의 유사도를 계산하는 알고리즘인 Word2Vec(Word to Vector)을 통해 유사 단어를 추출했다. 이렇게 도출된 유사 단어를 텍스트 분석 전문가 대상으로 성능 비교 투표를 진행했을 때, 한국어 뉴스보다 번역 전처리 기법이 적용된 영문 뉴스가 약 3배의 득표 차이로 의미있는 결과를 도출했다.

• Journal of the Korea Fashion and Costume Design Association
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• v.13 no.1
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• pp.147-158
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• 2011

This study analyzed the effective and suitable promotion method to increase visitors on the internet fashion soho shopping mall by surveying of female university students. The methods were in-depth interviews for 20 students and questionnaires for 363 students. The results indicated that the main routes of visiting the internet fashion shopping mall were keyword search window, banner advertisement window, and open market. Others were price comparison sites, the rank shop, fashion magazines or internet news, information in e-mail, broadcasting sponsor advertisements, name cards, and leaflets. So the effective methods to increase the number of visitors is to implement keyword advertisements, banner advertisements, and enter the open market to expose the brand names and item information. Being on price comparison sites or rank shops, advertisements in the fashion magazines, internet news or e-mail, broadcast sponsorships, and distribution of leaflets or name cards were also effective methods.

• International Journal of Computer Science & Network Security
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• v.21 no.11
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• pp.1-10
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• 2021

Cyberbullying has become a severe issue and brought a powerful impact on the cyber world. Due to the low cost and fast spreading of news, social media has become a tool that helps spread insult, offensive, and hate messages or opinions in a community. Detecting cyberbullying from social media is an intriguing research topic because it is vital for law enforcement agencies to witness how social media broadcast hate messages. Twitter is one of the famous social media and a platform for users to tell stories, give views, express feelings, and even spread news, whether true or false. Hence, it becomes an excellent resource for sentiment analysis. This paper aims to detect cyberbully threats based on Naïve Bayes, support vector machine (SVM), and k-nearest neighbour (k-NN) classifier model. Sentiment analysis will be applied based on people's opinions on social media and distribute polarity to them as positive, neutral, or negative. The accuracy for each classifier will be evaluated.