• Journal of Information Technology Applications and Management
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• v.22 no.2
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• pp.95-112
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• 2015

Spread of internet service had a huge effect on usage and spread of SNS world widely. Variety of the service has increased from human network managing to commerce, education, payment method and so on. Also, it is expanding its service territory to not only PC area but also that of mobile equipment with development of information technology. Spread of use on SNS provides existing corporations the expansion of service area. Late SNS starter companies are advancing in diverse way for attracting users by serving shopping, games and other services with association with SNS. Therefore, analysis on consumers' thought and pattern which analyze users' demand, service's function and contents and other factors in order to reflect on plans and operations of SNS is needed. On this perspective, this research is suggesting properties that are crucially related to sustained usage of SNS and study factors of SNS's characteristics that influence trust and satisfaction on SNS and continuous usage intent of SNS.

• Journal of Korea Society of Digital Industry and Information Management
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• v.9 no.4
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• pp.251-265
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• 2013

The emergence of social network services, is changing the foundation of human relationship formation and method of communication of individuals through sharing of free information. Social network service is a service to support or facilitate an on-line extension of off-line network among people by helping them to share personal profile. History of social network services very short. But users of the various layers is increasing rapidly and ripple effect social as a result is very large. The focus of existing research was mainly devoted to motivation of use and acceptance of social network services. Currently the use of SNS was maturing. Thus, in-depth research on the use pattern of SNS users is needed. The purpose of this study is that, for Facebook in social network services, to analyze the changes in the initial stage of use, medium-term, usage patterns at the current time. Results of the study by analyzing the characteristics of the change in the pattern of usage of user of Facebook, it can be used as basic materials for SNS researchers and service provider.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.2
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• pp.332-340
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• 2013

As a means for users to interact online, Social Network Service focuses on facilitating the building of social relation. Also, Social Network Service(SNS) provides various functions for managing relationships and sharing information based on relationships. Analyzing behavioral characteristics and the process of relationship formation can help to identify the characteristics of the model for online human relationship. In this paper, we analyze usage pattern based on characteristics posted messages of influential users in Twitter. Also, classifying Facebook users into influential group and uninfluential group based on the number of their social relations, we analyze and compare characteristics of relationship formation patterns of the two classified groups. In addition, we present characteristics of human relation model in social network according to the pattern analysis.

• Knowledge Management Research
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• v.16 no.3
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• pp.81-102
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• 2015

With the rapid development of digital media, there has been a huge change in a way of communication, a process of information diffusion and a role of traditional media. Not like mass media, social media enables users to generate and tap into the opinions of a larger world. From that reason, social media is impacting marketing strategies. However, still social media marketing researches just focus on case study, analysis of users motivation or analysis of power user's usage pattern. Word-of-mouth has always been important especially in marketing area. In social media, word-of-mouth depends on each user that's why this research focuses on individual user's activity in SNS. I defined 4 factors (produce, diffusion, network size, activity of network size enlarge) that are effect on activity and verified hypothesis by multiple regression analysis, hierarchical regression analysis and moderated multiple regression.

• Journal of the HCI Society of Korea
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• v.13 no.3
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• pp.43-53
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• 2018

Facebook, which has the largest number of users worldwide, has both positive and negative effects on our lives and society. The positive effects include social support from others, relationship building, entertainment, etc. In contrast, Facebook users also experience negative emotions such as tiredness and irritation, resulting in dissatisfaction as well as withdrawal from Facebook. The current study investigates both positive and negative effects of the use of by different demographic characteristics (i.e., age and gender), Facebook usage pattern (i.e., posters vs. lurkers), and Facebook usage time and frequency. The results show that (1) female users (vs. male users) feel higher level of fatigue and display stronger intention to discontinue Facebook. Moreover, (2) posters (vs. lurkers) feel higher level of positive emotions and social support, and stronger intention to continue Facebook. Lastly, (3) heavy users (vs. light users) exhibit higher level of positive emotions and stronger intentions to continue Facebook. This research sheds light on the fact that the characteristics of users affect individuals' intention to discontinue SNS and offers practical implications on the ever-expanding SNS market.

• Asia pacific journal of information systems
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• v.24 no.2
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• pp.233-253
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• 2014

Can the stock market really be predicted? Stock market prediction has attracted much attention from many fields including business, economics, statistics, and mathematics. Early research on stock market prediction was based on random walk theory (RWT) and the efficient market hypothesis (EMH). According to the EMH, stock market are largely driven by new information rather than present and past prices. Since it is unpredictable, stock market will follow a random walk. Even though these theories, Schumaker [2010] asserted that people keep trying to predict the stock market by using artificial intelligence, statistical estimates, and mathematical models. Mathematical approaches include Percolation Methods, Log-Periodic Oscillations and Wavelet Transforms to model future prices. Examples of artificial intelligence approaches that deals with optimization and machine learning are Genetic Algorithms, Support Vector Machines (SVM) and Neural Networks. Statistical approaches typically predicts the future by using past stock market data. Recently, financial engineers have started to predict the stock prices movement pattern by using the SNS data. SNS is the place where peoples opinions and ideas are freely flow and affect others' beliefs on certain things. Through word-of-mouth in SNS, people share product usage experiences, subjective feelings, and commonly accompanying sentiment or mood with others. An increasing number of empirical analyses of sentiment and mood are based on textual collections of public user generated data on the web. The Opinion mining is one domain of the data mining fields extracting public opinions exposed in SNS by utilizing data mining. There have been many studies on the issues of opinion mining from Web sources such as product reviews, forum posts and blogs. In relation to this literatures, we are trying to understand the effects of SNS exposures of firms on stock prices in Korea. Similarly to Bollen et al. [2011], we empirically analyze the impact of SNS exposures on stock return rates. We use Social Metrics by Daum Soft, an SNS big data analysis company in Korea. Social Metrics provides trends and public opinions in Twitter and blogs by using natural language process and analysis tools. It collects the sentences circulated in the Twitter in real time, and breaks down these sentences into the word units and then extracts keywords. In this study, we classify firms' exposures in SNS into two groups: positive and negative. To test the correlation and causation relationship between SNS exposures and stock price returns, we first collect 252 firms' stock prices and KRX100 index in the Korea Stock Exchange (KRX) from May 25, 2012 to September 1, 2012. We also gather the public attitudes (positive, negative) about these firms from Social Metrics over the same period of time. We conduct regression analysis between stock prices and the number of SNS exposures. Having checked the correlation between the two variables, we perform Granger causality test to see the causation direction between the two variables. The research result is that the number of total SNS exposures is positively related with stock market returns. The number of positive mentions of has also positive relationship with stock market returns. Contrarily, the number of negative mentions has negative relationship with stock market returns, but this relationship is statistically not significant. This means that the impact of positive mentions is statistically bigger than the impact of negative mentions. We also investigate whether the impacts are moderated by industry type and firm's size. We find that the SNS exposures impacts are bigger for IT firms than for non-IT firms, and bigger for small sized firms than for large sized firms. The results of Granger causality test shows change of stock price return is caused by SNS exposures, while the causation of the other way round is not significant. Therefore the correlation relationship between SNS exposures and stock prices has uni-direction causality. The more a firm is exposed in SNS, the more is the stock price likely to increase, while stock price changes may not cause more SNS mentions.

• Journal of Internet Computing and Services
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• v.15 no.2
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• pp.87-94
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• 2014

Social media which includes Facebook enable users to construct relationships and networks as well as sharing of information. By enlisting Facebook users as proxy, this paper attempted to analyze the different emotional states experienced by social media users, specifically to gauge what effect their usage motivation and usage pattern had on the ambivalence level of the users. The quantitative survey result revealed that usage duration or the time of day when Facebook was accessed had no relevant impact on one's ambivalence level. However, there was a direct correlation between frequency of Facebook usage and the ambivalence level. The more the user logged onto Facebook the more suppressed his or her expression became due to fear of giving negative impressions to others and also receiving their negative feedbacks, which then subsequently added to the user's ambivalence. People's main reasons for using Facebook were identified as "chatting," "communicating," "maintaining relationships," "relationship building," "networking," and "finding information about friends," but only "maintaining relationships," "communicating," and "networking" had observable effect on ambivalence. There were no noticeable differences among genders with regards to ambivalence and usage levels, but there was a marked difference based on the user's age. For example, people in their forties showed higher levels of ambivalence than those in their twenties. This may be attributed to anxiety they face as they use Facebook primarily to expand their networks and to maintain relationships. As such, it is surmised that their fatigue level from using social media will only increase. Meanwhile, Korean Facebook user's emotional manifestation tended to skew toward relation-involved ambivalence rather than the self-defensive type. This relation-involved ambivalence might be something that can actually help prevent damage to relationships by limiting excessive emotional expressions. In other words, such ambivalence by Facebook users may be a positive element in a user's social media interaction.

• The Journal of the Convergence on Culture Technology
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• v.9 no.6
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• pp.339-345
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• 2023

Design exists behind technology. Design is intertwined with the needs of daily life and market structures, and while dealing with technology, it can become insensitive to its meaning. Unlike other social media platforms, Instagram consists of image-based content. The purpose of this study is to examine the addictive design of Instagram. Furthermore, we discuss the ethical responsibilities that designers must have. A theoretical framework for understanding Instagram design is established through a review of major domestic and international literature that has been previously studied. Understand the history, structure, and functions of Instagram and identify Instagram designs that promote social media addiction. In this study, we introduced the mechanism by which Instagram promotes user addiction through design issues. (1) Pull-to-Refresh (2) Red color in push alarm (3) Profile photo border expression in Instagram Story. This design stimulates users' social desires and FOMO, forming the structure of obsessive Instagram usage habits. Instagram is an example that forces us to reconsider the ethical role of design and designers along with the advancement of technology. In today's world, the intrinsic value of what they create, including our society and life itself.