• Knowledge Management Research
• /
• v.19 no.1
• /
• pp.41-57
• /
• 2018

While there are lots of studies on examining the effects of social rapport in many research areas, however, there is a little work in examining the effect of the social rapport in social network service (SNS) contexts. Thus, this study attempts to examine the effect of social rapport in SNS settings. To address the research questions, this study has presented its hypotheses and conducted three experimental approaches by collecting 180 data from student subjects who have prior experiences on using SNSs to verify the hypotheses. This study has examined three experiments the effects of characteristics of Facebook(i.e. the number of mutual friends, the number of post likes, and the post personalities) on the social rapport and user responses. This study has conducted two-way ANOVA to verity its proposed research hypotheses. Based on three experiments, this study found that both the effects of the number of post likes and the number of post likes on the social rapport were not significant. Based upon empirical findings, this study has demonstrated how the effects of social rapports in SNSs were different from those of previous studies, and brought more attentions to the relevant literature.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.17 no.10
• /
• pp.2439-2446
• /
• 2013

Recently, SNS (Social Network Service) such as Twitter and Facebook has grown dramatically because of smart phones. Since development of IT has created massive information, social big data extremely increased. Competition between corporations is getting more intense, so they need customer feedback in order to fulfill an effective management. Because social big data plays an important role for getting customer feedback, a lot of corporations are interested in analyzing and applying of social big data. Collecting and analyzing social big data is operated by Buzz monitoring system. This paper demonstrates the research of buzz monitoring system that analyzes big data, and presents examples of customer reputation using buzz monitoring. In the paper, after all, it would analyze the result from the customer reputation, and research the implication.

• Journal of Information Technology Applications and Management
• /
• v.20 no.4
• /
• pp.263-278
• /
• 2013

SNS users have increased at rapid rate. Many firms are expected to use SNS, especially in marketing area. This study describes a SNS-based new products promotion case study. We aim to identify how differently SNS users respond to different types of SNS media or SNS contents. In this analysis marketing effects are measured in a number of website hits. The study result shows how the number of user's hits differs upon a combination of SNS media and SNS contents.

• Korean Journal of Family Social Work
• /
• no.58
• /
• pp.151-179
• /
• 2017

The purpose of this study was to evaluate the communication enhancement program through Social Network Service(SNS) of older adults in the community. This program was mainly designed for improving self-efficacy of older adults and enhancing their communication in the community by using SNS. This program was composed of several sub-programs; understanding the value of communication, meeting with SNS users, SNS education and practice, having activities with SNS, promoting SNS, holding public rehearsals and starting ceremony, and having off-line meeting. This study applied analytical framework based on logic model of systems theory, collected data from the subject group, and evaluated the sub-programs on dimensions of process and outcome. The results showed that this program has an effect on improving self-efficacy through participating SNS activities, enhancing communication through boosting SNS, creating new culture for older adults, and changing attitudes between generations. Based on these results, the practical guidelines for expanding the communication enhancement program through SNS, leading by older adults in the community, were suggested.

• Journal of Korea Multimedia Society
• /
• v.17 no.6
• /
• pp.671-680
• /
• 2014

Recently, with the remarkable increase of social network services, it is necessary to extract interesting information from lots of data about various individual opinions and preferences on SNS(Social Network Service). The sentiment information can be applied to various fields of society such as politics, public opinions, economics, personal services and entertainments. To extract sentiment information, it is necessary to use processing techniques that store a large amount of SNS data, extract meaningful data from them, and search the sentiment information. This paper proposes an efficient method to extract sentiment information from various unstructured big data on social networks using HDFS(Hadoop Distributed File System) platform and MapReduce functions. In experiments, the proposed method collects and stacks data steadily as the number of data is increased. When the proposed functions are applied to sentiment analysis, the system keeps load balancing and the analysis results are very close to the results of manual work.

• Fashion & Textile Research Journal
• /
• v.18 no.1
• /
• pp.48-62
• /
• 2016

Consumers have come to demand high quality, affordable prices, and innovative product designs of the outdoor wear market due to their well-being and leisure oriented lifestyle. A new system of business in outdoor wear has emerged in the process through which corporations have endeavored to satisfy such consumer needs. Outdoor wear brands have utilized social network services (SNS) such as Facebook and Twitter as means of marketing and have built close relations with consumers based on communication through these media. Recently, explosively escalating SNS data are referred to as social big data, and now that every consumer online is a commentator, reviewer, and publisher, the outdoor wear market and all of its brands have to stop talking and start listening to how they are perceived. Therefore, this study employs Social $Metrics^{TM}$, a social big data analysis solution by Daumsoft, Inc., to verify changes in the allusions related to outdoor wear market found on SNS. This study aims to identify changes in consumer perceptions of outdoor wear based on changes in outdoor wear search words and trends in positive and negative public opinion found in SNS social big data. In addition, products of interest, the major brands mentioned, the attributes taken into consideration during purchases of products, and consumers' psychology were categorized and analyzed by means of keywords related to outdoor wear brands found on SNS. The results of this study will provide fundamental resources for outdoor wear brands' market entry and brand strategy implementation in the future.

• Journal of Distribution Science
• /
• v.14 no.8
• /
• pp.35-44
• /
• 2016

Purpose - This study aims to understand the relationship between Chinese local SNS usage and social capital building through Chinese international students in South Korea. A research model that illustrates the relationship between the SNS usage (i.e., intensity, communication and social capital building is proposed. Based on the analysis, this study will provide responses to the question of if SNS really presents the danger of trapping international consumers in their local comfort zone or enhance social capital for the users. Research design, data, and methodology - The survey questionnaire is circulated among the WeChat (a Chinese local SNS) users who are the Chinese international students studying in South Korea. The collected data is analyzed by structural equation method using SPSS and AMOS. Results - Proposed hypotheses of the positive relationships between the attachment of SNS use and both individuals' bridging and bonding social capital are supported. It's also supported that (1) interpersonal communication, (2) interpersonal communication with old friends, and (3) interpersonal communication for making new friends on SNS positively influence individuals' bridging social capital. Conclusions - This paper demonstrates the importance of intensity of WeChat use and interpersonal communication that impact Chinese international students' bridging and bonding social capital on WeChat.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.9 no.8
• /
• pp.3203-3215
• /
• 2015

Due to the high growth of SNS population, service scalability is one of the critical issues to be addressed. The cloud environment provides the flexible computing and storage resources for services deployment, which fits the characteristics of scalable SNS deployment. However, if the SNS related information is not properly placed, it will cause unbalance load and heavy transmission cost on the storage virtual machine (VM) and cloud data center (CDC) network. In this paper, we characterize the SNS into a graph model based on the users' associations and interest correlations. The node weight represents the degree of associations, which can be indexed by the number of friends or data sources, and the link weight denotes the correlation between users/data sources. Then, based on the SNS graph, the two-step algorithm is proposed in this paper to determine the placement of SNS related data among VMs. Two k-means based clustering schemes are proposed to allocate social data in proper VM and physical servers for pre-configured VM and dynamic VM environment, respectively. The experimental example was conducted and to illustrate and compare the performance of the proposed schemes.

• The Korean Journal of Applied Statistics
• /
• v.31 no.5
• /
• pp.655-665
• /
• 2018

Social network services (SNS) have become the most common tool for the communication of public and private opinions as well as public issues; consequently, one may form or drive public opinions to advocate by spreading positive content using SNS. Controversy for survey data based opinion poll accuracy continues in relation to response rate or sampling methodology. This study suggests complementary measures that additionally consider the sentiment analysis results of unstructured data on a social network by data crawling and sentiment dictionary adjustment process. The suggested method shows the improvement of prediction accuracy by decreasing error rates.

• Journal of the Korea Convergence Society
• /
• v.6 no.6
• /
• pp.213-219
• /
• 2015

This study examines how the features of communication on Social Network Service(SNS) affect building faculty trust and long-term orientation in professor-student relationships. The research model was developed based on the previous research about communication, SNS and relationship development. The researcher surveyed 210 students to collect research data, and 195 questionnaires were analyzed using SmartPLS. The results indicate that the quality, frequency, interactivity and openness of communication on SNS affect positively on faculty trust. Moreover, the quality, frequency and openness of communication on SNS affect positively on long-term orientation, whereas interactivity does not. This mean that faculty trust plays a mediating role between interactivity and long-term orientation.