• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.12
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• pp.2885-2891
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• 2015

Twitter, one of online social network services, is one of the most popular micro-blogs, which generates a large number of automated programs, known as tweet bots because of the open structure of Twitter. While these tweet bots are categorized to legitimate bots and malicious bots, it is important to detect tweet bots since malicious bots spread spam and malicious contents to human users. In the conventional work, temporal information was utilized for the classficiation of human and bot. In this paper, by utilizing geo-tagged tweets that provide high-precision location information of users, we first identify both Twitter users' exact location and the corresponding timestamp, and then propose an improved two-stage tweet bot detection algorithm by computing an entropy based on spatio-temporal information. As a main result, the proposed algorithm shows superior bot detection and false alarm probabilities over the conventional result which only uses temporal information.

• Fashion & Textile Research Journal
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• v.17 no.6
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• pp.942-955
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• 2015

Hashtag has emerged and become one of cultural trend. Given that more and more firms in the fashion industry are using hashtag on images based on SNS to provide information of their products and to communicate with their customers. Especially, hashtags through voluntary participation of users provides the perspective of how customers consume their products. Therefore, this study focused on the using motives of hashtag in image based SNS with customer social participation as mediator towards brand equity. The purpose of this study is (1) to investigate the usage motivation of hashtag of image contents based SNS, (2) to expose how each usage motive affects customer social participation and (3) to find out how customer social participation has an effect on brand equity. In order to achieve the objectives of this study, first we conducted an in-depth interview on 8 image based SNS heavy users to understand the using motives of hashtags. Furthermore, we conducted online surveys amongst people aged between 20s and 30s of image contents based SNS users. As a result of this study, followings were figured out. First, four of usage motivation of hashtag were examined through in-depth interview and previous studies; interest sharing, social interaction, ease of use and enjoyment. Second, usage motivation of hashtag has a significant effect on customer social participation. Third, customer-media participation and customer-customer participation impact positively on brand equity. Lastly, level of customer social participation has the moderating effect on the relationship between motivation of hashtag and customer social participation.

• Journal of Internet Computing and Services
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• v.15 no.5
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• pp.63-72
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• 2014

Twitter has been a popular social media platform where people post short messages of 140 characters or less via the web. A hashtag is a word or acronym created by Twitter users to open a discussion about certain topics and issues that have a very high percentage of trending. Since the hashtag posts are sorted by time, not relevancy, people who firstly use Twitter have had difficulty understanding their context. In this paper, we propose a HBase-based automatic summary system in order to reduce the difficulty of understanding. The proposed system combines an automatic summary method with a fuzzy system after storing the streaming data provided by Twitter API to the HBase. Throughout this procedure, we have eliminated the duplicate of contents in the hashtag posts and have computed scores between posts so that the users can access to the trending topics with relevancy.

• Design Convergence Study
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• v.14 no.4
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• pp.209-221
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• 2015

This study investigates in depth of the new marketing trend, in which social media, an effective marketing tool for promoting a new product, and gamification technic of engaging consumers in communication, are combined. Although gamification has been applied to various fields for a long time, conventional way of applying gamification is different from when it is combined with socialmedia. Therefore, this study examines the background and characteristics of the convergence phenomena between the social media and gamification based on the theoretical consideration of the social media and gamification. Then, the cases of social media marketing utilizing gamification are analyzed and classified into general participation, active participation, creative behavior, networking, and experiential type according to the user's different levels and ways of participation. As a result, when the social media and gamification are combined, the change of an aspect is found to be more meaningfully influential to today's consumers as in competition - achievement - relationship, compared to the conventional way of game mechanics. This study has significance in the way that it established a useful basis for the marketing strategy through the study of the new game mechanics that has been applied to social media marketing utilizing gamification.

• Cartoon and Animation Studies
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• s.40
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• pp.423-442
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• 2015

In a digital environment that is keep in change content from smart phones to tablet PC are a social network service is holding deep place in our lives. Social networking applications has building a network and communication with others than other application, it means that Social networking applications are sharing not only personal purpose in that trend of variety and competition of these social networks can be expected to trend and be developed thru analysis of user certification. this study of social network service application is proposed to developing of application thru analyze the two-effective application which is high ranked in google store. the theoretical foundation was set based on the seven elements of the social network service of the information structures designed by Jean Smith. This study proceeded analysis is for the functional elements of Facebook and Instagram, and the advantages and disadvantages through survey research. As a result of the empirical analysis to user of Instagram and face book of communication, identity, satisfaction for the group are equally. Instagram is about the presence, reputation, and Facebook has had a high level of satisfaction for each sharing and relationship. Facebook got high satisfaction from sharing features, but user feel of discomfort in the randomly showing advertising content. Instagram is not showing off advertise on common page of content, it is good point to be complementary to facebook. And, Instagram hashtag is good for convenience, but satisfaction is high with Facebook. in order to increase the satisfaction of Instagram, it is necessary to consider the main advantage of the communication and the functional aspects of the share from facebook.

• KIPS Transactions on Software and Data Engineering
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• v.6 no.11
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• pp.521-526
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• 2017

Data format of Big data is diverse and vast, and its generation speed is very fast, requiring new management and analysis methods, not traditional data processing methods. Textual mining techniques can be used to extract useful information from unstructured text written in human language in online documents on social networks. Identifying trends in the message of politics, economy, and culture left behind in social media is a factor in understanding what topics they are interested in. In this study, text mining was performed on online news related to a given keyword using topic - oriented analysis technique. We use Latent Dirichiet Allocation (LDA) to extract information from web documents and analyze which subjects are interested in a given keyword, and which topics are related to which core values are related.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.2
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• pp.157-162
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• 2008

This paper presents a learning method of tagging ontology using large tagging data such as a folksonomy, which stands for classification structure informally created by the people. There is no common agreement about the semantics of a tagging, and most social web sites internally use different methods to represent tagging information, obstructing interoperability between sites and the automated processing by software agents. To solve this problem, we need a tagging ontology, defined by analyzing intrinsic attributes of a tagging. Through several machine learning for tagging data, tag groups and similar user groups are extracted, and then used to learn the tagging ontology. A recommender system adopting the tagging ontology is also suggested as an applying field.

• Journal of Korean Society for Geospatial Information Science
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• v.23 no.1
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• pp.23-29
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• 2015

In this study, the spatial relevance between the regional housing price data and the spatial distribution of the location-based social media data is explored. The spatial analysis with rasterization was applied to this study, because the both data have a different form to analyze. The geo-tagged Twitter data had been collected for a month and the regional housing price index about sales and lease were used. The spatial range of both data includes Seoul and the some parts of the metropolitan area. 2,000m grid was constructed to consider the different spatial measure between two data, and they were combined into the constructed grids. The Hotspot Analysis was operated using the combined dataset to see the comparison of spatial distribution, and the bivariate spatial correlation coefficients between two data were measured for the quantitative analysis. The result of this study shows that Seocho-gu area is detected as a common hotspot of tweet and housing sales price index data. though the spatial relevance is not detected between tweet and housing lease price index data.

• Journal of the Korea Society of Computer and Information
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• v.19 no.1
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• pp.95-110
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• 2014

The purpose of this research is to further investigate the influence of partnership between with the mediator effect of the social business on the outcome of SCM. IT technology fusion electronic tags, mobile phone, such as cloud computing is also activated in supply chain management of recently, business is faster, if social business is applied here that are smarter, customers or suppliers, there may be communication directly and to further improve the relationship partnership. 150 questionnaires were sent to companies that have introduced SCM to their systems and are operating it. Among 150 questionnaires, 127 collected data were analyzed excluding incomplete 23 data. Statistical methods used in this study were frequency analysis, factor analysis, reliability analysis, t-test, ANOVA, path analysis, Scheffe test and Sobel test with Amos 18.0. and SPSS 21.0. The analytical results are as follows. First, the more the reliability, information share, continuous transaction, effects on the social business are getting higher, the interdependence has little impact on it. Second, the impact on the outcome of SCM, partnerships between companies, showed a significant influence the reliability, the share of information, the continuous transaction, but the interdependence was analysed as an uninfluential factor. Third, the social business is analyses to have a mediator effect in relationship between the partnership and the outcome of SCM.

• Knowledge Management Research
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• v.23 no.3
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• pp.65-88
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• 2022

Companies actively engage with the public through social media to enhance sales and promote brand awareness, which was further encouraged by the pandemic. However, previous studies tend to consider companies as a group of identical features. This study focuses on the differences between B2B and B2C companies' social media content strategy in relation to user engagement. This study categorized KOSPI 100 companies that manage Facebook corporate fan pages into B2B and B2C, and then analyzed the contents they posted from January 1 to December 31, 2020. The result showed that B2C companies tended to use videos over images, prefer hashtags, and comment its product name more often compared to B2B companies. B2B companies preferred images, used more hyperlinks, and mentioned its company name more often. In B2B companies, images and length of text had positive effects on user engagement, while hyperlink and URL had negative effects. B2C companies' text length had positive effect on user engagement. This study provides practical implications to PR practitioners for establishing a social media strategy which enhances user engagement.