• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.2
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• pp.583-600
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• 2014

Social media is considered a valuable platform for gathering and analyzing the collective and subconscious opinions of people in Internet and mobile environments, where they express, explicitly and implicitly, their daily preferences for brands and products. Extracting and tracking the various attitudes and concerns that people express through social media could enable us to categorize brands and decipher individuals' cognitive decision-making structure in their choice of brands. We investigate the cognitive network structure of consumers by building an inter-category map through the mining of big data. In so doing, we create an improved online recommendation model. Building on economic sociology theory, we suggest a framework for revealing collective preference by analyzing the patterns of brand names that users frequently mention in the online public sphere. We expect that our study will be useful for those conducting theoretical research on digital marketing strategies and doing practical work on branding strategies.

• Journal of Korea Multimedia Society
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• v.17 no.6
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• pp.671-680
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• 2014

Recently, with the remarkable increase of social network services, it is necessary to extract interesting information from lots of data about various individual opinions and preferences on SNS(Social Network Service). The sentiment information can be applied to various fields of society such as politics, public opinions, economics, personal services and entertainments. To extract sentiment information, it is necessary to use processing techniques that store a large amount of SNS data, extract meaningful data from them, and search the sentiment information. This paper proposes an efficient method to extract sentiment information from various unstructured big data on social networks using HDFS(Hadoop Distributed File System) platform and MapReduce functions. In experiments, the proposed method collects and stacks data steadily as the number of data is increased. When the proposed functions are applied to sentiment analysis, the system keeps load balancing and the analysis results are very close to the results of manual work.

• Journal of Information Technology Applications and Management
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• v.24 no.2
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• pp.1-15
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• 2017

Social Network Service (SNS) emerged to become a major platform for consumers' social activities, affecting their choice behavior. With rapid increase in SNS adoption among consumers, firms actively apply SNS into their marketing activities and use it as an important communication medium with consumers. Particularly SNS marketing become increasingly prevalent in Chinese restaurant sector as they provide promotional information to consumers through SNS. It is urgent for firms to understand the extent of SNS impact on consumers' choice behavior, and to understand consumers' response toward SNS in order to develop more effective SNS marketing strategies. The purpose of this study is to assess the effects of four SNS characteristics on brand equity and purchase intention and to determine the relative importance among these four characteristics on brand equity and purchase intention. Results show that all of the characteristics have significant influence on consumers' brand equity, and also, brand equity affects consumers' purchase intention.

• International Journal of Computer Science & Network Security
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• v.23 no.5
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• pp.1-6
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• 2023

Text mining (TM) is most widely used to process the various unstructured text documents and process the data present in the various domains. The other name for text mining is text classification. This domain is most popular in many domains such as movie reviews, product reviews on various E-commerce websites, sentiment analysis, topic modeling and cyber bullying on social media messages. Cyber-bullying is the type of abusing someone with the insulting language. Personal abusing, sexual harassment, other types of abusing come under cyber-bullying. Several existing systems are developed to detect the bullying words based on their situation in the social networking sites (SNS). SNS becomes platform for bully someone. In this paper, An Enhanced text mining approach is developed by using Ensemble Algorithm (ETMA) to solve several problems in traditional algorithms and improve the accuracy, processing time and quality of the result. ETMA is the algorithm used to analyze the bullying text within the social networking sites (SNS) such as facebook, twitter etc. The ETMA is applied on synthetic dataset collected from various data a source which consists of 5k messages belongs to bullying and non-bullying. The performance is analyzed by showing Precision, Recall, F1-Score and Accuracy.

• Asia Marketing Journal
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• v.22 no.3
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• pp.71-85
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• 2020

Social media has emerged as a major hub of engagement between brands and consumers in recent years, and allows user-generated content to serve as a powerful means of encouraging communication between the sides. However, it is challenging to negotiate user-generated content owing to its lack of structure and the enormous amount generated. This study focuses on the hashtag, a metadata tag that reflects customers' brand perception through social media platforms. Online users share their knowledge and impressions using a wide variety of hashtags. We examine hashtags that co-occur with particular branded hashtags on the social media platform, Instagram, to derive insights about brand perception. We apply text mining technology and network analysis to identify the perceptions of brand images among consumers on the site, where this helps distinguish among the diverse personalities of the brands. This study contributes to highlighting the value of hashtags in constructing brand personality in the context of online marketing.

• Journal of Information Technology Services
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• v.18 no.3
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• pp.95-115
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• 2019

In recent years, social media that has emerged with the development of network technology has changed the channels of information dissemination. The social Q&A community is a platform for knowledge-sharing activities in a question-and-answer manner based on Web 2.0. In knowledge-sharing activities, valuable new knowledge continues to be produced and will surely bring great benefits to individuals or businesses. In the social Q&A community, the user's subjective factors play a crucial role in influencing the user's continued use and participation in knowledge-sharing activities. In order for users to actively participate in knowledge-sharing activities in the community, it needs to grasp their subjective ideas. This study explores the issue of sharing knowledge by users of the social Q&A community "Zhihu", or how to drive community revitalization efforts from these. The three factors self-efficacy, self-development motivation, and social comparison tendencies were derived, and identify their relationship with knowledge-sharing activities and community-boosting efforts through empirical analysis. In addition, the influence of knowledge acquisition on knowledge provision was investigated through sense of reciprocity. Implications of the study findings and the future research directions were also discussed.

• Proceedings of the Korean Society of Computer Information Conference
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• 2013.07a
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• pp.259-260
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• 2013

최근 SNS가 급속히 성장하고 있다. 본 논문에서는 불특정 다수가 아닌 한 명을 대상으로 하는 안드로이드 기반 SNS 어플리케이션을 제안한다. 제안한 폐쇄형 SNS는 상대방 번호를 입력해 단 한명만 지정할 수 있는 어플리케이션이다. D-day기능을 이용한 기념일 관리와 사진 공유 관리가 가능하며 Wish List를 통해 상대방의 관심사도 알 수 있는 등 다양한 커뮤니케이션이 가능하다.

• Proceedings of the Korea Contents Association Conference
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• 2012.05a
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• pp.41-42
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• 2012

e-Sports가 국내에서 활성화되기 위해서는 첫째, 온라인 게임에 대한 부정적 인식이 전환되어야 하고, 둘째, 모든 스포츠 종목이 대중화하기 위해 필수적인 미디어의 역할이 중요하다. 이 연구에서는 소셜 네트워크 시스템 기반의 e-Sports 플랫폼을 제안한다. 이 시스템은 e-Sports 선수를 적절히 매칭하여 전체 게임의 수익을 극대화하는 지능형 매칭 시스템과 1인 미디어 융합한다, 특히 한국 고유의 PC방 문화에 접목시키는 방안도 분석된다.

• Proceedings of the Korean Society of Disaster Information Conference
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• 2015.11a
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• pp.92-95
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• 2015

본 논문에서는 다양한 사회재난 대응을 위해 IoT 기술을 활용한 개방형 플랫폼 기술을 제안하고자 한다. 기존 재난 대응 시스템의 문제점을 분석하여 적응성, 확장성, 개방성을 가진 시스템 구조를 오픈 IoT 기술인 모비우스를 통해 구현하고 복합 감지 구조를 통해 상황 판단 정확도와 신뢰성을 높이는 기술을 제안하였다.

• Annual Conference of KIPS
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• 2011.04a
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• pp.1489-1491
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• 2011

최근 스마트폰과 SNS(Social Network Service)에 대한 관심이 증가하고 있다. 본 논문에서는 불특정 다수가 아닌 특정 그룹을 대상으로 하는 안드로이드 기반 SNS 어플리케이션인 MMSNS를 제안한다. MMSNS에서는 사용자들이 속한 그룹에서 인적 네트워크를 형성할 수 있도록 도우며 서로 글을 게시하고 열람하고, 쪽지를 보내는 등 커뮤니케이션이 가능하다. 본 논문에서는 MMSNS의 기능을 소개하고 구현 결과를 보인다.