• Proceedings of the Korea Information Processing Society Conference
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• 2011.04a
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• pp.544-546
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• 2011

Due to the explosive growth of online social network users, large numbers of users discover these social network sites are a place where they can be able to spend their spare time, share feelings, ideas freely, and to search for new friends or partners. These web sites give an opportunity for its users to socialize with new people and to keep in touch or reconnect with current or old friends and families across disperse continents via these web sites, which traditionally replace the traditional methods. These social network web sites need careful investigations and findings on the usability for effective interactivity and more usability. However, little research might have previously invested on the usability of these on social network web sites. Therefore, we propose a new framework to study the usability of these social network sites. We namely call our framework "Interactivity". This framework will enable us to assess the usability of the social network sites. It will provide an overview of the user's behavior while interacting in these social network web sites. Measurement of the interactivity will be measured using Camtasia software. This software will entirely capture the interactivity of users including the screen and the movements, which the screen and the motion of the user action will undergo to analysis at the end of our research.

• The Korean Journal of Franchise Management
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• v.2 no.2
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• pp.24-44
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• 2011

Many companies are increasingly using social network service(SNS) as an online marketing tool, and its marketing activation has been in the limelight as a differentiation strategy most recently. The purpose of this study is to analyze online marketing cases utilizing SNS and to apply it in Franchise Enterprise in order to activate its marketing activities. This study is more concerned with the cases of facebook, twitter, and blog among social network services and suggests some ways of utilizing them in Franchise Enterprise as follows: Based on the examples of facebook, firstly, we set up the role as a homepage in individul, Franchise Enterprise, and other organizations. Secondly, we also set up the role as an organizing tool in communities, and thirdly, setting up the role as a location map tool. Regarding some applications in marketing tool of Franchise Enterprise, we suggest the role as a public relation tool of the company and brand, and also propose the role of brand planning and development. Finally, we suggest a way of overcoming the limitation in offline operations.

• Journal of Korea Multimedia Society
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• v.17 no.2
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• pp.180-190
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• 2014

Social network services are increasingly being used in organizational settings to improve relationships among employees and enhance prospects for information exchange and cooperative work. Social Networking Service(SNS) has deeply penetrated organizational job settings, influencing multiple aspects of employee's life. This study is designed to explore the impact of SNS engagement on the job performance mediated as team cooperation and decision making quality effects. Data were collected from 146 employees who use organizational SNS in there company. Factor analysis and structural equation method are employed. Results from a survey accompanied by the substantial impacts of organizational employee's social networking engagement on social learning processes and outcomes. SNS engagement not only directly influences organizational employee's job performance, but also helps their team cooperation and decision making quality from others and adapt to organizational culture, both of which play prominent roles in improving their job performance.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.11
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• pp.4994-5004
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• 2012

This paper aims at investigating voluntary user participation such as user citizenship behavior and aberrant user behavior in the SNS context. Also it examines on how user participation behavior affects social connectedness, privacy concern, and user satisfaction. The empirical assessment of the research model was conducted using a total of 143 responses. The findings show that user citizenship behavior impacts on social connectedness positively and significantly whereas aberrant user behavior does not influence on social connectedness. Aberrant user behavior is proven not to be related to social connectedness, and to has positive relationship with concern for privacy invasion. Also, the results show that privacy concern is not associated with social connectedness. Finally, social connectedness is shown to be a key determinant of SNS user satisfaction whereas privacy concern is not related to user satisfaction.

• 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.

• Journal of Intelligence and Information Systems
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• v.20 no.1
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• pp.49-65
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• 2014

Word of Mouth (WOM) is a behavior used by consumers to transfer or communicate their product or service experience to other consumers. Due to the popularity of social media such as Facebook, Twitter, blogs, and online communities, electronic WOM (e-WOM) has become important to the success of products or services. As a result, most enterprises pay close attention to e-WOM for their products or services. This is especially important for movies, as these are experiential products. This paper aims to identify the network factors of an online movie community that impact box office revenue using social network analysis. In addition to traditional WOM factors (volume and valence of WOM), network centrality measures of the online community are included as influential factors in box office revenue. Based on previous research results, we develop five hypotheses on the relationships between potential influential factors (WOM volume, WOM valence, degree centrality, betweenness centrality, closeness centrality) and box office revenue. The first hypothesis is that the accumulated volume of WOM in online product communities is positively related to the total revenue of movies. The second hypothesis is that the accumulated valence of WOM in online product communities is positively related to the total revenue of movies. The third hypothesis is that the average of degree centralities of reviewers in online product communities is positively related to the total revenue of movies. The fourth hypothesis is that the average of betweenness centralities of reviewers in online product communities is positively related to the total revenue of movies. The fifth hypothesis is that the average of betweenness centralities of reviewers in online product communities is positively related to the total revenue of movies. To verify our research model, we collect movie review data from the Internet Movie Database (IMDb), which is a representative online movie community, and movie revenue data from the Box-Office-Mojo website. The movies in this analysis include weekly top-10 movies from September 1, 2012, to September 1, 2013, with in total. We collect movie metadata such as screening periods and user ratings; and community data in IMDb including reviewer identification, review content, review times, responder identification, reply content, reply times, and reply relationships. For the same period, the revenue data from Box-Office-Mojo is collected on a weekly basis. Movie community networks are constructed based on reply relationships between reviewers. Using a social network analysis tool, NodeXL, we calculate the averages of three centralities including degree, betweenness, and closeness centrality for each movie. Correlation analysis of focal variables and the dependent variable (final revenue) shows that three centrality measures are highly correlated, prompting us to perform multiple regressions separately with each centrality measure. Consistent with previous research results, our regression analysis results show that the volume and valence of WOM are positively related to the final box office revenue of movies. Moreover, the averages of betweenness centralities from initial community networks impact the final movie revenues. However, both of the averages of degree centralities and closeness centralities do not influence final movie performance. Based on the regression results, three hypotheses, 1, 2, and 4, are accepted, and two hypotheses, 3 and 5, are rejected. This study tries to link the network structure of e-WOM on online product communities with the product's performance. Based on the analysis of a real online movie community, the results show that online community network structures can work as a predictor of movie performance. The results show that the betweenness centralities of the reviewer community are critical for the prediction of movie performance. However, degree centralities and closeness centralities do not influence movie performance. As future research topics, similar analyses are required for other product categories such as electronic goods and online content to generalize the study results.

• Journal of Intelligence and Information Systems
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• v.22 no.4
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• pp.193-215
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• 2016

In recent years, the proliferation of diverse social networking services has led users to use many mediums simultaneously depending on their individual purpose and taste. Besides, while collecting information about particular themes, they usually employ various mediums such as social networking services, Internet news, and blogs. However, in terms of management, each document circulated through diverse mediums is placed in different categories on the basis of each source's policy and standards, hindering any attempt to conduct research on a specific category across different kinds of sources. For example, documents containing content on "Application for a foreign travel" can be classified into "Information Technology," "Travel," or "Life and Culture" according to the peculiar standard of each source. Likewise, with different viewpoints of definition and levels of specification for each source, similar categories can be named and structured differently in accordance with each source. To overcome these limitations, this study proposes a plan for conducting category mapping between different sources with various mediums while maintaining the existing category system of the medium as it is. Specifically, by re-classifying individual documents from the viewpoint of diverse sources and storing the result of such a classification as extra attributes, this study proposes a logical layer by which users can search for a specific document from multiple heterogeneous sources with different category names as if they belong to the same source. Besides, by collecting 6,000 articles of news from two Internet news portals, experiments were conducted to compare accuracy among sources, supervised learning and semi-supervised learning, and homogeneous and heterogeneous learning data. It is particularly interesting that in some categories, classifying accuracy of semi-supervised learning using heterogeneous learning data proved to be higher than that of supervised learning and semi-supervised learning, which used homogeneous learning data. This study has the following significances. First, it proposes a logical plan for establishing a system to integrate and manage all the heterogeneous mediums in different classifying systems while maintaining the existing physical classifying system as it is. This study's results particularly exhibit very different classifying accuracies in accordance with the heterogeneity of learning data; this is expected to spur further studies for enhancing the performance of the proposed methodology through the analysis of characteristics by category. In addition, with an increasing demand for search, collection, and analysis of documents from diverse mediums, the scope of the Internet search is not restricted to one medium. However, since each medium has a different categorical structure and name, it is actually very difficult to search for a specific category insofar as encompassing heterogeneous mediums. The proposed methodology is also significant for presenting a plan that enquires into all the documents regarding the standards of the relevant sites' categorical classification when the users select the desired site, while maintaining the existing site's characteristics and structure as it is. This study's proposed methodology needs to be further complemented in the following aspects. First, though only an indirect comparison and evaluation was made on the performance of this proposed methodology, future studies would need to conduct more direct tests on its accuracy. That is, after re-classifying documents of the object source on the basis of the categorical system of the existing source, the extent to which the classification was accurate needs to be verified through evaluation by actual users. In addition, the accuracy in classification needs to be increased by making the methodology more sophisticated. Furthermore, an understanding is required that the characteristics of some categories that showed a rather higher classifying accuracy of heterogeneous semi-supervised learning than that of supervised learning might assist in obtaining heterogeneous documents from diverse mediums and seeking plans that enhance the accuracy of document classification through its usage.

• Journal of Intelligence and Information Systems
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• v.17 no.1
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• pp.127-138
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• 2011

The core service of most research portal sites is providing relevant research papers to various researchers that match their research interests. This kind of service may only be effective and easy to use when a user can provide correct and concrete information about a paper such as the title, authors, and keywords. However, unfortunately, most users of this service are not acquainted with concrete bibliographic information. It implies that most users inevitably experience repeated trial and error attempts of keyword-based search. Especially, retrieving a relevant research paper is more difficult when a user is novice in the research domain and does not know appropriate keywords. In this case, a user should perform iterative searches as follows : i) perform an initial search with an arbitrary keyword, ii) acquire related keywords from the retrieved papers, and iii) perform another search again with the acquired keywords. This usage pattern implies that the level of service quality and user satisfaction of a portal site are strongly affected by the level of keyword management and searching mechanism. To overcome this kind of inefficiency, some leading research portal sites adopt the association rule mining-based keyword recommendation service that is similar to the product recommendation of online shopping malls. However, keyword recommendation only based on association analysis has limitation that it can show only a simple and direct relationship between two keywords. In other words, the association analysis itself is unable to present the complex relationships among many keywords in some adjacent research areas. To overcome this limitation, we propose the hybrid approach for establishing association network among keywords used in research papers. The keyword association network can be established by the following phases : i) a set of keywords specified in a certain paper are regarded as co-purchased items, ii) perform association analysis for the keywords and extract frequent patterns of keywords that satisfy predefined thresholds of confidence, support, and lift, and iii) schematize the frequent keyword patterns as a network to show the core keywords of each research area and connecting keywords among two or more research areas. To estimate the practical application of our approach, we performed a simple experiment with 600 keywords. The keywords are extracted from 131 research papers published in five prominent Korean journals in 2009. In the experiment, we used the SAS Enterprise Miner for association analysis and the R software for social network analysis. As the final outcome, we presented a network diagram and a cluster dendrogram for the keyword association network. We summarized the results in Section 4 of this paper. The main contribution of our proposed approach can be found in the following aspects : i) the keyword network can provide an initial roadmap of a research area to researchers who are novice in the domain, ii) a researcher can grasp the distribution of many keywords neighboring to a certain keyword, and iii) researchers can get some idea for converging different research areas by observing connecting keywords in the keyword association network. Further studies should include the following. First, the current version of our approach does not implement a standard meta-dictionary. For practical use, homonyms, synonyms, and multilingual problems should be resolved with a standard meta-dictionary. Additionally, more clear guidelines for clustering research areas and defining core and connecting keywords should be provided. Finally, intensive experiments not only on Korean research papers but also on international papers should be performed in further studies.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.05a
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• pp.469-471
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• 2017

Those who travel to another area for work or travel acquire cquire information through various media such as Internet websites before going to the area. The way to determine whether the information you collect is reliable is to go directly to that area. However, many users may overlook the date the post was posted. when you arrive at a delicious restaurant for a travel purpose, it can happen that the restaurant is gone. In order for Smartphone Users to be able to provide reliable information about a specific region through an application, it is possible to receive information from a specific local user using the application through crowd sourcing techniques. Collect suggestions from users when there are changes in the same area, rather than accepting indiscriminate information and when duplicate content exists, it is marked on the application map so that it can be viewed by other users. It provides not only simple restaurant information, but also area-specific information such as additional information about tourist attractions or information on restrooms to solve physiological phenomena that may occur in the area where they first arrive. Application users can get information about nearby public facilities and restaurants on a GPS basis.

• Journal of Intelligence and Information Systems
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• v.25 no.3
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• pp.141-160
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• 2019

Agile methodologies in software development, including the development of artificial intelligence software, have been widespread over the past several years. In spite of the popularity of agile methodologies in practice, there is a lack of empirical evidence to identify determinants of success of software projects in which agile methods are used. To understand the role of clients in software project where agile methods are used, we examine the effect of client-side factors, including lack of user involvement, unrealistic client expectations, and constant changes of requirements on project success from practitioners' perspective. Survey methods are used in this study. Data were collected by means of online survey to IT professionals who have experience with software development methodologies, and ordered logit regression is used to analyze the survey data. Results of our study imply the following managerial findings. First, user involvement is critical to project success to take advantage of agile methods. Second, it is interesting that, with an agile method, constant changes of client's requirements is not a negative factor but a positive factor of project success. Third, unrealistic client expectations do negatively affect project success even with agile methods.