• Journal of Korea Society of Industrial Information Systems
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• v.20 no.1
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• pp.19-26
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• 2015

Recently, a lot of users are using social network services as the spread of SNS and generalization of smart-phone. In this study, we apply clustering and ranking method for finding twitter influential users. First, we propose five ranking elements. The five elements include the number of follow, the number of retweet, IRP, IFP and influ-score. These elements are used by centroid point of clustering methods. This study can help to find novel approaches for finding twitter influential users.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.2
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• pp.1016-1025
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• 2015

This study tried to identify the influential users of college sports teams' Twitter accounts and categorize them into three groups including an official account, media account, and layperson account. A total of 14 Twitter accounts at NCAA Division 1 universities were selected through convenience sampling method. In men's sports, the greatest number of influential users was layperson account followed by media account and official account. In women's sports, the greatest number of influential users was layperson account followed by official account and media account. The results provided the insight of college sports online social network and will expand the growing literature on social media in sport and offer practical data for marketers to use social media more effectively.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.24 no.4
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• pp.75-90
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• 2013

Given the context that users are actively using social media with multimedia embedded information, the purpose of this study is to demonstrate how images are used within Twitter messages, especially in influential and favorited messages. In order to achieve the purpose of this study, the top 200 influential and favorited messages with images were selected out of 1,589 tweets related to "Boston bombing" in April 2013. The characteristics of the message, image use, and user are analyzed and compared. Two phases of the analysis were conducted on three data sets containing the top 200 influential messages, top 200 favorited messages, and general messages. In the first phase, coding schemes have been developed for conducting three categorical analyses: (1) categorization of tweets, (2) categorization of image use, and (3) categorization of users. The three data sets were then coded using the coding schemes. In the second phase, comparison analyses were conducted among influential, favorited, and general tweets in terms of tweet type, image use, and user. While messages expressing opinion were found to be most favorited, the messages that shared information were recognized as most influential to users. On the other hand, as only four image uses - information dissemination, illustration, emotive/persuasive, and information processing - were found in this data set, the primary image use is likely to be data-driven rather than object-driven. From the perspective of users, the user types such as government, celebrity, and photo-sharing sites were found to be favorited and influential. An improved understanding of how users' image needs, in the context of social media, contribute to the body of knowledge of image needs. This study will also provide valuable insight into practical designs and implications of image retrieval systems or services.

• The Journal of the Korea Contents Association
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• v.16 no.4
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• pp.455-465
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• 2016

The purpose of this study was to examine the effect of twitter influenctials on users' willingness on express opinions. Based on the spiral of silence and corrective action hypothesis, the contradictory hypotheses were drawn. The online expeiment was conducted to verify which hypothesis is valid. Participant were assigned to the four experimenatal conditons: a famous influential's twit which agrees with the issue; a famous influential's twit which disagrees with the issue; an ordinary influential's twit to agree with the issue; an ordinary influential's twit to disagree with the issue. Results showed that opinion congruency with a twitter influential did not influence participants' willingness to express opinion online and offline, but the interaction effect with the type of influentials was found. Opinion dissonance with an ordinary tiwtterian increased willingness to express opinion. The findings suggest that twitter influentials, particulary an ordinary influentials with differnet opinions, can motivate users to express their own opinion.

• Journal of Information Processing Systems
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• v.13 no.4
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• pp.987-999
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• 2017

Extraction of influential people from their respective domains has attained the attention of scholastic community during current epoch. This study introduces an innovative interaction strength metric for retrieval of the most influential users in the online social network. The interactive strength is measured by three factors, namely re-tweet strength, commencing intensity and mentioning density. In this article, we design a novel algorithm called IPRank that considers the communications from perspectives of followers and followees in order to mine and rank the most influential people based on proposed interaction strength metric. We conducted extensive experiments to evaluate the strength and rank of each user in the micro-blog network. The comparative analysis validates that IPRank discovered high ranked people in terms of interaction strength. While the prior algorithm placed some low influenced people at high rank. The proposed model uncovers influential people due to inclusion of a novel interaction strength metric that improves results significantly in contrast with prior algorithm.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.6
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• pp.2069-2085
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• 2021

A Social Networking Service (SNS) platform provides digital footprints to discover users' interests and track the social diffusion of product adoptions. How to identify a small set of seed users in a SNS who is potential to adopt a new promoting product with high probability, is a key question in social networks. Existing works approached this as a social influence maximization problem. However, these approaches relied heavily on text information for topic modeling and neglected the impact of seed users' relation in the model. To this end, in this paper, we first develop a general product adoption function integrating both users' interest and social influence, where the user interest model relies on historical user behavior and the seed users' evaluations without any text information. Accordingly, we formulate a product adoption maximization problem and prove NP-hardness of this problem. We then design an efficient algorithm to solve this problem. We further devise a method to automatically learn the parameter in the proposed adoption function from users' past behaviors. Finally, experimental results show the soundness of our proposed adoption decision function and the effectiveness of the proposed seed selection method for product adoption maximization.

• Journal of Korea Society of Digital Industry and Information Management
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• v.7 no.2
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• pp.185-203
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• 2011

In recent years, blogs have become important resources for information sharing; and tourism blogs are providing a new way of sharing tour experiences. Blogs are becoming very popular amongst web users to share their life experiences with other web users around the world. Specifically the goals of this research are; (1) to suggest theory framework of acceptance and user satisfaction about toruism blogs based on TAM, (2) to examine relationships between exogenous variables and (3) to suggest effectiveness of tourism blogs in a marketing perspective. The research model and hypotheses were developed based on the theories of technology acceptance model. Questionnaire was used to collect data. The analysis of this study is designed as individual level to examine the causal relationship among variables. The the reliability and validity of data was tested by explanatory factor analysis, Cronbach's alpha coefficient, confirmatory factor analysis, and correlation analysis. Also, the structural equation model(SEM) analysis was performed to test the usefulness of the model. The analysis results revealed that interaction, entertainment, system quality and information quality are major influential variables on the perceived usefulness of tourism blog. Also, entertainment and system quality are influential variables on the perceived ease of use of tourism blog.

• The Journal of Society for e-Business Studies
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• v.17 no.4
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• pp.69-93
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• 2012

Various influence-related relationships in Social Network Services (SNS) among users, posts, and user-and-post, can be expressed using links. The current research evaluates the influence of specific users or posts by analyzing the link structure of relevant social network graphs to identify influential users. We applied the concept of mutual interactions proposed for ranking semantic web resources, rather than the voting notion of Page Rank or HITS, to blogosphere, one of the early SNS. Through many experiments with network models, where the performance and validity of each alternative approach can be analyzed, we showed the applicability and strengths of our approach. The weight tuning processes for the links of these network models enabled us to control the experiment errors form the link weight differences and compare the implementation easiness of alternatives. An additional example of how to enter the content scores of commercial or spam posts into the graph-based method is suggested on a small network model as well. This research, as a starting point of the study on identifying influential users in SNS, is distinctive from the previous researches in the following points. First, various influence-related properties that are deemed important but are disregarded, such as scraping, commenting, subscribing to RSS feeds, and trusting friends, can be considered simultaneously. Second, the framework reflects the general phenomenon where objects interacting with more influential objects increase their influence. Third, regarding the extent to which a bloggers causes other bloggers to act after him or her as the most important factor of influence, we treated sequential referencing relationships with a viewpoint from that of PageRank or HITS (Hypertext Induced Topic Selection).

• ETRI Journal
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• v.37 no.2
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• pp.417-427
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• 2015

With recent advances in media technology, the creation of a relatively new service, N-screen, has been realized. N-screen provides seamless connections among various media and enables users to enjoy entertainment content at any time and any location. With such recent advances comes opportunity; therefore, for those N-screen service providers who have established an early edge in the ICT industry, it is imperative that they maintain this and stay ahead of the ensuing competition. In this context, the objective of this study is two-fold; first, we aim to find factors influencing the behavior of existing and potential N-screen service users, and then second, to examine the differences in how these factors operate within the two user types. The results of this study show that the perceived value and subjective norm are important influencers in both user types. However, price fairness and innovativeness are only influential on the attitude and intention of potential users, while some aspects of media usage have only significant influences on the behavior and loyalty of existing users. Based on these results, we provide some implications for both researchers and practitioners who wish to better understand the nature of N-screen users.

• International Journal of Contents
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• v.15 no.4
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• pp.74-81
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• 2019

This study examined the overall relationship between information privacy concern, need for uniqueness (NFU), and disclosure behavior to explain the personal factors that drive data-sharing on Facebook. The results of an online survey conducted with 222 Facebook users show that among diverse data that social media users disclose online, four distinct factors are identified: basic personal data, private data, personal opinions, and personal photos. In general, there is a negative relationship between privacy concern and a positive relationship between the NFU and the willingness to self-disclose information. Overall, the NFU was a better predictor of willingness to disclose information than privacy concern, gender, or age. While privacy concern has been identified as an influential factor when users evaluate social networking sites, the findings of this study contribute to the literature by demonstrating that an individual's need to manifest individualization on social media overrides privacy concerns.