• 한국노년학
• /
• v.36 no.3
• /
• pp.711-726
• /
• 2016

The purpose of this study was to analyze to 1) the differences according to demographic characteristics 2) select the type-specific communities online channels of the baby boomer customers group, who ever search for restaurant information through on-line for the previous three months. The study was based on a total of 280 samples obtained from on-line networking service users in a metropolitan area from April 15 to 30, 2016. The major findings are as follows. The data were analysed using frequency, factor analysis, cluster analysis and ${\chi}^2test$. According to the results of factor analysis, on-line utilizing attributes were separated into three factors: commitment of useful information, activity of leading on-line, and habit. The based on a factor analysis, cluster analysis was adopted to segment baby boomer customers. The identified four clusters showed in using on-line: type of active utilization, habit, seeking information and passive utilization. The clusters had significant differences in gender and monthly income by demographics. All of four clusters selected blog, face book, twitter in turn through the personal on-line channels. Cluster type of active utilization and habit selected restaurant home pages, restaurant blog, restaurant face book, restaurant twitter in turn through the public on-line channels. Cluster type of seeking information and passively utilization selected restaurant home pages, restaurant blog, restaurant twitter, restaurant face book in turn through the public on-line channels. Implications and future research were also discussed.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.12 no.5
• /
• pp.169-175
• /
• 2012

The Great East Japan Earthquake left some implications. Especially the case of alerting by social media had present. This paper suggests system for posting earthquake information to microblog like twitter and me2day. Microblog is most efficient and effective social media. So, this system receive earthquake information from the Earthquake Broadcast System in the Korea Meteorological Administration and post the information to twitter and me2day. By this system, earthquake information can be notice easily and response can be checked.

• Journal of Advanced Navigation Technology
• /
• v.16 no.1
• /
• pp.82-88
• /
• 2012

In recent years, social awareness and concern about the SNS is getting a lot and many researches on the social impact of the SNS and variety strategies using SNS have emerged one after another. In this paper, we explain the method of interlocking between SNS and variety sensors in physical computing environment. Especially we propose that interlocking technology between sensors and twitter in Arduino platform(open source environment) can be used for the handicapped people. We design a way to send message via twitter for handicapped people using values from various sensors.

• Journal of Information Management
• /
• v.42 no.4
• /
• pp.225-242
• /
• 2011

With the development of the IT and internet, companies try to use Blogs, Twitter, Facebook, smart phone for their marketing and customer relationship management. What is called social media marketing appear and it lead to new value creation to the company. However, until now most of libraries in Korea didn't have much interest in marketing and PR. In recent, libraries are starting to be interested in marketing and social network service. Library try to use social network service for marketing. This research introduces the various cases and status of using social network service for marketing in Korea and international library field, analyzes these cases from a marketing perspective. Finally, this research suggests the considerations and successful strategy for using social media marketing in library field.

• Proceedings of the Korean Society of Computer Information Conference
• /
• 2020.01a
• /
• pp.15-18
• /
• 2020

특정 영화의 스크린 독과점이 꾸준히 논란이 되고 있다. 본 논문에서는 영화 스크린 분배의 불평등성을 지적하고 이에 대한 개선을 요구할 근거로 머신러닝 기법을 활용한 영화 관람객 예측 모델을 제안한다. 이에 따라 KOBIS, 네이버 영화, 트위터, 구글 트렌드에서 수집한 3,143개의 영화 데이터를 이용하여 랜덤포레스트와 그라디언트 부스팅 기법을 활용한 영화 관람객 예측 모델을 구현하였다. 모델 평가 결과, 그라디언트 부스팅 모델의 RMSE는 600,486, 랜덤포레스트 모델의 RMSE는 518,989로 랜덤포레스트 모델의 예측력이 더 높았다. 예측력이 높았던 랜덤포레스트 모델을 활용, 상영관을 크게 확보하지 못 했던 봉준호 감독의 영화 '옥자'의 상영관 수를 조절하여 관람객 수를 예측, 6,345,011명이라는 결과를 제시한다.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
• /
• v.14 no.4
• /
• pp.199-209
• /
• 2019

The importance of business strategy for successful social media engagement has quickly increased as more businesses engage in social media. The importance is even greater for startup companies because startup companies are genuinely new to business, and they need to increase their presence in the market, and quickly access future customers. The objective of this paper lies in exploring key indicators of social media engagements by selected startup companies. The key indicators include two aspects of social media usages by the companies: i) overall social media activities, and ii) properties of network structure of the information flow platform provided by social media service. To better assess and evaluate the key indicators of social media usages by startup companies, the indicators will be compared with those of selected large established companies. Twitter is selected as a social media service for the analysis of this paper, and using Twitter REST API, data regarding the key indicators of overall Twitter activities and the Twitter follower-network of each company in the sample are collected. Then, the data are analyzed using social network analysis and hierarchical clustering analysis to examine the characteristics of the follower-network structures and to compare the characteristics between startup companies and established companies. The results show that most indicators are significantly different across startup companies and established companies. One key interesting finding is that the startup companies have proportionally more influencers in their follower-networks than the established companies have. Another interesting finding is that the follower-networks of startup companies in the sample have higher modularity and higher transitivity, suggesting that the startup companies tend to have a proportionally larger number of communities of users in their follower-networks, and the users in the networks are more tightly connected and cohesive internally. The key business implication for the future social media engagement efforts by startup companies in general is that startup companies may need to focus on getting more attention from influencers and promoting more cohesive communities in their follower-networks to appreciate the potential benefits of social media in the early stage of business of startup companies.

• Journal of Korean Library and Information Science Society
• /
• v.46 no.3
• /
• pp.225-253
• /
• 2015

This study investigated the interactions between archives and users based on content analysis of posts of Facebook and Twitter operated by archival institutions. It focused on posts in official Facebooks and Twitters of the U.S. and the U.K. national archives. The posts included 66 in Facebook and 670 in Twitter of the U.S. national archives, as well as 73 in Facebook and 84 in Twitter of the U.K. national archive. The analysis showed that information sharing of in-house collections and online resources, as well as information dissemination of events were the most common interaction types of the posts. 1 and 1 communication or information gathering such as questionnaire or vote rarely happened. In addition, the extent of users' responses was great on posts regarding information sharing of in-house collections. Providing information about people or events with timely manners motivated interests and participations of users. It is necessary to consider various types of interactions that facilitate user engagement. It is also important to make efforts to provide timely records in connection with exiting web resources and a variety of social media provided by archival institutions.

• Journal of Internet Computing and Services
• /
• v.13 no.6
• /
• pp.9-16
• /
• 2012

Social Network Service (SNS) such as Twitter and Facebook has explosively grown nationwide since iPhone was introduced to Korea in 2009. In addition, KakaoStory has recently opened and joined to the SNS market, and it has grown to one of the most popular SNS in the domestic market in a short period of time. Social Network Service supports not only the formation of relationship between SNS users in common interests but also various activities such as management of personal connections and the sharing of information or contents. These three types of SNS have several common functions of sharing and distributing various contents rooted on the personal relationship formed through SNS. As each SNS user has specific reasons for the use of each service, a survey was conducted targeting those who use all of Twitter, Facebook, and KakaoStory was drawn by the statistical analyses of survey answers on users' reasons for each service. This result of study suggests factors to consider in order to exploit a new SNS or to enhance an existing service and can be used as a standard of which SNS for users to select for their own different purposes. It will also provide the basic data for the trust formation, one of the ethics in the upcoming Social Era.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.24 no.3
• /
• pp.292-297
• /
• 2014

As a Social Network Service (SNS) has become an integral part of our everyday lives, millions of users can express their opinion and share information regardless of time and place. Hence sentiment analysis using micro-blogs has been studied in various field to know people's opinion on particular topics. Most of previous researches on movie reviews consider only positive and negative sentiment and use it to predict movie rating. As people feel not only positive and negative but also various emotion, the sentiment that people feel while watching a movie need to be classified in more detail to extract more information than personal preference. We measure sentiment distributions of each movie from tweets according to the Thayer's model. Then, we find similar movies by calculating similarity between each sentiment distributions. Through the experiments, we verify that our method using micro-blogs performs better than using only genre information of movies.

• Journal of Internet Computing and Services
• /
• v.12 no.2
• /
• pp.113-122
• /
• 2011

Social Network Service(SNS) has become a hot trend as a web service which helps users construct social relationships in the web and enables online communication. The information about user activities and behaviors obtained from the SNSs is expected to be an useful knowledge source for other services such as recommendation services. Most of previous researches on SNS rely on analyzing overall network topology and surveying the activities in a one-dimensional aspect. This paper propose a system for measuring multi-dimensional interaction through the activities in a SNS. The proposed system delivers an unified profile (consisting of profile and multi-dimension interaction) model from user-activities in Twitter.com. At the experimental section, some meaningful perspectives on a set of the unified profiles are described.