• Journal of Digital Convergence
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• v.13 no.4
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• pp.395-404
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• 2015

This study is exploring objective awareness of literary therapy by consideration of popular perception about literary therapy through analysis of big data. The purpose of this study is the deduction of meaning information through analysis in the viewpoint of big data at online social network service(SNS) about 'literary therapy'. Accordingly, the main way of research became content analysis of keyword linked to literary therapy by utilizing opinion mining method related to text mining. The study mainly grasped 'literary therapy' and analyzed 'bibliotherapy' comparatively. The period of study was from Oct. 10th to Nov. 10th, 2014(during 30 days), and SNS such as blog or twitter became the subject of search. Through the result of study analysis, the conclusion that the spread of literary therapeutic prospect, structural harmony of literary therapeutic field, and the solidity of perceptional axis about literary therapy are needed can be drawn. This study is worthwhile because it can investigate popular awareness about literary therapy and can suggest alternative for invigoration of literary therapy.

• Information Systems Review
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• v.13 no.1
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• pp.33-59
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• 2011

Although online social network services widely used in human networking and recruiting industries, it is showing off its limitations in followings-it's hard to reach the status of seamless connection between offline and online; the incompletion and low credibility of the information came from non-face-to-face profile exchange; and the restraint of user autonomy due to centralized control. This paper defines the ubiquitous social network management which enables the seamless real-time face-to-face social interactions of the users based on WPAN (Wireless Personal Area Network) who share the same interest in real word and deduces a ubiquitous social network management framework based on it. As an instance of ubiquitous social network management, u-Recruiting service model will be designed and analyzed. The Analysis using the business model will be followed by the possible scenario of service model. The role, value proposition and potential benefits of the each participants in this service model and will be given as well. In order to evaluate relative advantages of the model suggested by this study, 6 cases will be compared.

• Journal of Digital Convergence
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• v.17 no.3
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• pp.107-117
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• 2019

In the era of SNS, many people relies on it to express their emotions about various kinds of products and services. Therefore, for the companies eagerly seeking to investigate how their products and services are perceived in the market, emotion mining tasks using dataset from SNSs become important much more than ever. Basically, emotion mining is a branch of sentiment analysis which is based on BOW (bag-of-words) and TF-IDF. However, there are few studies on the emotion mining which adopt feature selection (FS) methods to look for optimal set of features ensuring better results. In this sense, this study aims to propose FS methods to conduct emotion mining tasks more effectively with better outcomes. This study uses Twitter and SemEval2007 dataset for the sake of emotion mining experiments. We applied three FS methods such as CFS (Correlation based FS), IG (Information Gain), and ReliefF. Emotion mining results were obtained from applying the selected features to nine classifiers. When applying DT (decision tree) to Tweet dataset, accuracy increases with CFS, IG, and ReliefF methods. When applying LR (logistic regression) to SemEval2007 dataset, accuracy increases with ReliefF method.

• The Journal of Society for e-Business Studies
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• v.25 no.4
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• pp.33-60
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• 2020

Along with the rapid advance in internet technologies, ubiquitous mobile device usage has enabled consumers to access real-time information and increased interaction with others through various social media. Consumers can now get information more easily when making purchase decisions, and these changes are affecting the brand landscape. In a digitally connected world, brand image is not communicated to the consumers one-sidedly. Rather, with consumers' growing influence, it is a result of co-creation where consumers have an active role in building brand image. This explains a reality where people no longer purchase products just because they know the brand or because it is a famous brand. However, there has been little discussion on the matter, and many practitioners still rely on the traditional measures of brand indicators. The goal of this research is to present the limitations of traditional definition and measurement of brand and brand image, and propose a more direct and adequate measure that reflects the nature of a connected world. Inspired by the proverb, "A man is known by the company he keeps," the proposed measurement offers insight to the position of brand (or brand image) through co-purchased product networks. This paper suggests a framework of network analysis that clusters brands of cosmetics by the frequency of other products purchased together. This is done by analyzing product networks of a brand extracted from actual purchase data on Amazon.com. This is a more direct approach, compared to past measures where consumers' intention or cognitive aspects are examined through survey. The practical implication is that our research attempts to close the gap between brand indicators and actual purchase behavior. From a theoretical standpoint, this paper extends the traditional conceptualization of brand image to a network perspective that reflects the nature of a digitally connected society.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.9 no.4
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• pp.1-12
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• 2014

It is essential factor for business operation to raise funds effectively. However, in Korea, many start-ups and small businesses have difficulties in fund-raising. In recent years, crowdfunding, a new method for funding a project of individuals or organizations by raising monetary contributions from a large number of people, has been growing up simultaneously with diffusion of social media. Crowdfunding is on early stage in Korea, and the majority of projects are focused on cultural or art categories. There is high proportion of projects that have social value in start-up sector. Crowdfunding in Korea has great potential because success rate of it is much higher than its of advanced countries, although market size is much smaller than them. The purpose of this paper is to propose success strategies of crowdfunding for start-up through case study. 5 crowdfunding platforms of Korea and Kickstarter, the platform of United States were investigated. Then we checked the figures related to the operation of the whole Korean projects on start-up. Finally, we made comparison between the cases of success and failure by analyzing 8 project characteristics. The study shows that it were the differences in trustworthiness and activeness of project creator, value of reward and efforts for interactivity that have great effects on success of the project. Whereas there was no significant influence of societal contribution and sponsor engagement. The thesis provides success strategies of crowdfunding for start-up as follows. Firstly, creator of the project should make support base by enthusiastic activites before launching funding project. Secondly, there should be contents that can easily show the process of business development in the project information. Thirdly, there must be appropriate design of rewards for each amounts of support money. Finally, efforts for interactivity, such as frequent updates, response for comments and SNS posting, should be followed after the launch of the project.

• Journal of Intelligence and Information Systems
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• v.19 no.4
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• pp.133-146
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• 2013

While the use of internet is routine nowadays, users receive and share information through a variety of media. Through the use of internet, information delivery media is diversifying from traditional media of one-way communication, such as newspaper, TV, and radio, into media of two-way communication. In contrast of traditional media, blogs enable individuals to directly upload and share news, which can be considered to have a differential speed of information diffusion than news media that convey information unilaterally. Therefore this Study focused on the difference between online news and social media blogs. Moreover, there are variations in the speed of information diffusion because that information closely related to one person boosts communications between individuals. We believe that users' standard of evaluation would change based on the types of information. As well, the speed of information diffusion would change based on the level of proximity. Therefore, the purpose of this study is to examine the differences in information diffusion based on the types of media. And then information is segmentalized and an examination is done to see how information diffusion differentiates based on the types of information. This study used the Bass diffusion model, which has been frequently used because this model has higher explanatory power than other models by explaining diffusion of market through innovation effect and imitation effect. Also this model has been applied a lot in other information diffusion related studies. The Bass diffusion model includes an innovation effect and an imitation effect. Innovation effect measures the early-stage impact, while the imitation effect measures the impact of word of mouth at the later stage. According to Mahajan et al. (2000), Innovation effect is emphasized by usefulness and ease-of-use, as well Imitation effect is emphasized by subjective norm and word-of-mouth. Also, according to Lee et al. (2011), Innovation effect is emphasized by mass communication. According to Moore and Benbasat (1996), Innovation effect is emphasized by relative advantage. Because Imitation effect is adopted by within-group influences and Innovation effects is adopted by product's or service's innovation. Therefore, ours study compared online news and social media blogs to examine the differences between media. We also choose different types of information including entertainment related information "Psy Gentelman", Current affair news "Earthquake in Sichuan, China", and product related information "Galaxy S4" in order to examine the variations on information diffusion. We considered that users' information proximity alters based on the types of information. Hence, we chose the three types of information mentioned above, which have different level of proximity from users' standpoint, in order to examine the flow of information diffusion. The first conclusion of this study is that different media has similar effect on information diffusion, even the types of media of information provider are different. Information diffusion has only been distinguished by a disparity between proximity of information. Second, information diffusions differ based on types of information. From the standpoint of users, product and entertainment related information has high imitation effect because of word of mouth. On the other hand, imitation effect dominates innovation effect on Current affair news. From the results of this study, the flow changes of information diffusion is examined and be applied to practical use. This study has some limitations, and those limitations would be able to provide opportunities and suggestions for future research. Presenting the difference of Information diffusion according to media and proximity has difficulties for generalization of theory due to small sample size. Therefore, if further studies adopt to a request for an increase of sample size and media diversity, difference of the information diffusion according to media type and information proximity could be understood more detailed.

• The KIPS Transactions:PartB
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• v.18B no.5
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• pp.325-332
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• 2011

Social Network Services(SNS) such as Twitter, Facebook and Myspace have gained popularity worldwide. Especially, sentiment analysis of SNS users' sentence is very important since it is very useful in the opinion mining. In this paper, we propose a new sentiment classification method of sentences which contains formal and informal vocabulary such as emoticons, and newly coined words. Previous methods used only formal vocabulary to classify sentiments of sentences. However, these methods are not quite effective because internet users use sentences that contain informal vocabulary. In addition, we construct suggest to construct domain sentiment vocabulary because the same word may represent different sentiments in different domains. Feature vectors are extracted from the sentiment vocabulary information and classified by Support Vector Machine(SVM). Our proposed method shows good performance in classification accuracy.

• The Journal of the Korea Contents Association
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• v.12 no.7
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• pp.336-345
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• 2012

Under the influence of information technology, there has been a significant change in the consumers' attitude and behavior toward the cultural products. Especially, the social network service (SNS) is predicted to effectively facilitate the growing interaction among potential consumers, which may lead to consumption of the cultural products. The goal of this study is thus two-fold: (a) to investigate the characteristic features of the digital environments based on SNS, and (b) to examine how these factors result in the purchase of the cultural contents. The survey data identified the digital environments as Informational interaction, Information connectivity, and Informational trust in the SNS environment. Subsequently, the structural equation methods confirmed that these factors facilitate consumers' participation in the information network and promote consumers' emotional attachment to the cultural contents, which eventually lead to the positive attitude toward the purchase of the cultural contents.

• Journal of Intelligence and Information Systems
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• v.19 no.1
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• pp.125-139
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• 2013

Big data refers to the data that cannot be processes with conventional contemporary data technologies. As smart devices and social network services produces vast amount of data, big data attracts much attention from researchers. There are strong demands form governments and industries for bib data as it can create new values by drawing business insights from data. Since various new technologies to process big data introduced, academic communities also show much interest to the big data domain. A notable advance related to the big data technology has been in various fields. Big data technology makes it possible to access, collect, and save individual's personal data. These technologies enable the analysis of huge amounts of data with lower cost and less time, which is impossible to achieve with traditional methods. It even detects personal information that people do not want to open. Therefore, people using information technology such as the Internet or online services have some level of privacy concerns, and such feelings can hinder continued use of information systems. For example, SNS offers various benefits, but users are sometimes highly exposed to privacy intrusions because they write too much personal information on it. Even though users post their personal information on the Internet by themselves, the data sometimes is not under control of the users. Once the private data is posed on the Internet, it can be transferred to anywhere by a few clicks, and can be abused to create fake identity. In this way, privacy intrusion happens. This study aims to investigate how perceived personal information overload in SNS affects user's risk perception and information privacy concerns. Also, it examines the relationship between the concerns and user resistance behavior. A survey approach and structural equation modeling method are employed for data collection and analysis. This study contributes meaningful insights for academic researchers and policy makers who are planning to develop guidelines for privacy protection. The study shows that information overload on the social network services can bring the significant increase of users' perceived level of privacy risks. In turn, the perceived privacy risks leads to the increased level of privacy concerns. IF privacy concerns increase, it can affect users to from a negative or resistant attitude toward system use. The resistance attitude may lead users to discontinue the use of social network services. Furthermore, information overload is mediated by perceived risks to affect privacy concerns rather than has direct influence on perceived risk. It implies that resistance to the system use can be diminished by reducing perceived risks of users. Given that users' resistant behavior become salient when they have high privacy concerns, the measures to alleviate users' privacy concerns should be conceived. This study makes academic contribution of integrating traditional information overload theory and user resistance theory to investigate perceived privacy concerns in current IS contexts. There is little big data research which examined the technology with empirical and behavioral approach, as the research topic has just emerged. It also makes practical contributions. Information overload connects to the increased level of perceived privacy risks, and discontinued use of the information system. To keep users from departing the system, organizations should develop a system in which private data is controlled and managed with ease. This study suggests that actions to lower the level of perceived risks and privacy concerns should be taken for information systems continuance.

• The Journal of Society for e-Business Studies
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• v.20 no.1
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• pp.1-22
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• 2015

Due to recent growth in IT industry along with the expansion of smartphone, we came to connect to the Internet wherever and whenever we are. However, this causes negative side effects, though. One of them is a rapid increase of the financial crimes such as the Phishing and the SMishing. There have been many on-going researches about crimes such as Phishing and SMishing to protect users. However, the study about sharing knowledge on SNS to prevent such a crime can be hardly found. Based on social identity theory, we conduct the research about factors on SNS users' intention to share the information security knowledge on SNS. As a result, we found that knowledge provision self-efficacy has a significant impact on self-expression. In addition, it also found out self-expression, awareness about information security and the sense of belonging have a significant impact respectively on the intention to share the information security knowledge on SNS. On the other hand, the altruism didn't have a significant impact to the intention to share information security knowledge on SNS. With this research as a starting point, it seems necessary to expand its range to all types of online community in the future for the generalization of the hypotheses.