• Annual Conference on Human and Language Technology
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• 2013.10a
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• pp.33-38
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• 2013

소셜미디어를 통한 여론분석과 브랜드 모니터링에 대한 요구가 증가하면서, 빅데이터로부터 감성을 분석하는 기술에 대한 필요가 늘고 있다. 이를 위해, 본 논문에서는 단순 긍/부정 감성이 아닌 20종류의 세분화된 감성을 분석하기 위한 감성어휘 구축 알고리즘을 제시한다. 감성어휘 구축을 위해서는 준지도학습을 사용하였으며, 도메인에 특화되지 않은 일반 감성어휘를 구축하도록 학습되었다. 학습된 감성어휘를 인물, 스마트기기, 정책 등 다양한 도메인의 트위터 데이터에 적용하여 세부감성을 분석한 결과, 알고리즘의 특성상 재현율이 낮다는 한계를 가지고 있었으나, 대부분의 감성에 대해 높은 정확도를 지닌 감성어휘를 구축할 수 있었고, 감성을 직간접적으로 나타내는 표현들을 학습할 수 있었다.

• Smart Media Journal
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• v.5 no.2
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• pp.8-14
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• 2016

In this paper, we propose a model for coaching and formal operating procedures performed capstone design advisor during the design done to allow effective guidance and management. Coaching model is proposed through coaching and capstone design proposed by coaching on the procedure for the implementation and management, Mokpo National University Department of Computer Engineering student in the program outcomes, performance assessment of the effective operation of the capstone design based social network service the demonstrated effectiveness of the coaching model.

• Proceedings of the Korea Contents Association Conference
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• 2019.05a
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• pp.289-290
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• 2019

최근 뷰티에 대한 관심이 증가함으로써 화장품 관련 정보가 대량으로 발생하였다. 사용자는 선택적으로 정보를 얻고자 하기 때문에 사용자 맞춤형 추천 서비스가 부각되고 있다. 본 논문에서는 소셜 미디어 환경에서 기계 학습을 활용한 화장품 추천 시스템을 설계하고 구현한다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.1
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• pp.1-7
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• 2021

Investor mood from social media is gaining increasing attention for leading a price movement in stock market. Based on the behavioral finance theory, this study argues that sentiment extracted from social media using big data technique can predict a real-time (short-run) price momentum in Chinese stock market. Collecting Sina Weibo posts that related to COVID-19 using keyword method, a daily influential weighted sentiment factors is extracted from the sizable raw data of over 2 millions of posts. We examine one supervised and 4 unsupervised sentiment analysis model, and use the best performed word-frequency and BiLSTM mdoel. The test result shows a similar movement between stock price change and sentiment factor. It indicates that public mood extracted from social media can in some extent represent the investors' sentiment and make a difference in stock market fluctuation when people are concentrating on a special events that can cause effect on the stock market.

• The KIPS Transactions:PartA
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• v.18A no.6
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• pp.233-240
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• 2011

In this paper, we design and implement an L-SNS system to reduce ever-increasing adverse effects of the Internet through the strengths of social network service system based on media literacy, including critical comprehension, creative expression, participation, communication ability, etc. The L-SNS system we proposed here was used the Smartphone as a medium of communication for learners, and to let them have indirect experience and real-time interaction. In addition, it provides the environment to make objective decisions through the process examining an in-depth discussion among other learners in the aspect of a third party.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.11
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• pp.541-548
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• 2016

The use of social media is already essential as a source of information for listening user's various opinions and monitoring. We define social 'risks' that issues effect negative influences for public opinion in social media. This paper aims to discriminate various linguistic features and reveal their effects for building an automatic classification model of social risks. Expecially we adopt a word embedding technique for representation of linguistic clues in risk sentences. As a preliminary experiment to analyze characteristics of individual features, we revise errors in automatic linguistic analysis. At the result, the most important feature is NE (Named Entity) information and the best condition is when combine basic linguistic features. word embedding, and word clusters within core predicates. Experimental results under the real situation in social bigdata - including linguistic analysis errors - show 92.08% and 85.84% in precision respectively for frequent risk categories set and full test set.

• The Journal of Bigdata
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• v.4 no.1
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• pp.99-118
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• 2019

This study used network analysis and clustering techniques to analyze studies on social media participation. As a result of the main path analysis, 37 major studies were extracted and divided into two networks: community-related networks and new media-related. Network analysis and clustering result in four clusters. This study has the academic significance of using academic data to grasp research trends at a macro level and using network analysis and machine learning as a methodology.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.05a
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• pp.890-892
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• 2014

최근 스마트기기가 널리 보급되고 소셜네트워크 서비스가 확산되면서, 스마트 기기 및 소셜미디어를 활용함으로서 학습에서 상호작용을 극대화한 교육환경으로 스마트러닝이 크게 부각되고 있다. 그리고 스마트러닝 콘텐츠 및 환경의 확산으로 PC 위주에서 스마트폰 등으로 이러닝 콘텐츠의 사용환경이 확장됨에 따라 콘텐츠 저작의 경제성과 효율성 등을 고려하게 되었으며, 하나의 콘텐츠를 다양한 환경에서 활용 가능하도록 하고 있다. 그러나 기존 PC기반의 콘텐츠를 스마트기기에 적용함에 있어 여러 가지 문제가 발생하는데 이 문제들을 해결하는 방안으로 먼저 콘텐츠에 대한 표준화가 중요한 요소로 작용한다. 따라서 본 논문에서는 전자책 표준화를 활용한 효율적인 스마트러닝 기법을 제시하고자 한다.

• Journal of Digital Convergence
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• v.10 no.3
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• pp.273-281
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• 2012

As appearing on the stage of social media which expands the private relations to the public relations, the Social Intelligence(SI) is made again prominent in our society. The Public Relations(PR) is in particular related to the SI which means the ability to get along well with other people and to encourage others to cooperate with oneself. It points out the necessity of the study with respect to the impact of SI on the choice of educational major and the adaptation of social media in PR, because the SI is one of the important aptitudes which students who major in Communication and PR would need for actual field. But the result of the research indicates that the SI does not influence the choice of educational major of the students who major in Communication and PR. To make those students go into high level of the SI, the students need the specific education which would enhance and reinforce their SI such as the SPACE Program developed by Albrecht and reorganization of curriculum in the education of Communication and PR. Besides, this study shows that the high level people actively use the social media, for example, Smartphone in order to keep their best relationships.

• Journal of Digital Convergence
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• v.14 no.4
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• pp.111-128
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• 2016

The purpose of this study was to analyze domestic research trends of social learning in higher education, and find out educational implications with regard to the effectiveness of social learning. The 63 articles on social learning were finally analyzed, which were published in KCI journals. The results are as follows: Firstly, in respect of research contents, the research area of utilization and the survey methods were most frequently used in those studies. Secondly, as to the use of SNS, the analyzed studies were centralized on Facebook and Formal Structured Learning. Thirdly, as for the effectiveness of SNS, the experimental studies showed that social learning has an effective impact on the learning outcomes, learning processes, and learners' characteristics. In addition, survey studies most frequently set the independent variables as learners' characteristics and the dependent variables as participation, satisfaction, and academic achievement. This research has a significance in terms of verifying the educational implications of social learning, and providing the preliminary data to facilitate the performance for the effective social learning.