• Journal of the Korean Society for information Management
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• v.24 no.1 s.63
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• pp.227-250
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• 2007

With the advent of social networking activity on the Internet, online community sites are becoming more popular. The main purpose of this study is to empirically investigate the influence of intermediary trust and system trust on the forum activity trust and information quality satisfaction. We assume that the intermediary trust and system trust come from the online community site itself, while the forum activity is made within a specific forum allowed on the online community site, and therefore forum activity trust and information quality satisfaction are related to a specific forum. The 591 valid questionnaire data were gathered from the users acting in forums allowed on the Samsung Economic Research Institute (SERI) (www. seri.org). The empirical results are as follows. First, the SERI intermediary trust and its system trust have positive influence on the SERI forum information quality, system quality, and perceived effectiveness. Second, the SERI intermediary trust contributes to reducing the SERI forum perceived risks, while the SERI system quality does not. Third, the higher the SERI intermediary trust is, the higher the SERI forum trust and information quality satisfaction increase.

• Journal of Internet Computing and Services
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• v.13 no.1
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• pp.65-74
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• 2012

Cloud services are used for improving business. Moreover, customer relationship management(CRM) approaches use social networking as tools to enhance services to customers. However, most cloud systems do not support the semantic structures, and because of this, vital information from social network sites is still hard to process and use for business strategy. This paper proposes a collaboration framework based on social semantic web for cloud system. The proposed framework consists of components to support social semantic web to provide an efficient collaboration system for cloud consumers and service providers. The knowledge acquisition module extracts rules from data gathered by social agents and these rules are used for collaboration and business strategy. This paper showed the implementations of processing of social network site data in the proposed semantic model and pattern extraction which was used for the virtual grouping of cloud service providers for efficient collaboration.

• The Research Journal of the Costume Culture
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• v.25 no.1
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• pp.88-103
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• 2017

The rapid growth in the popularity of social media sites has meant that social media has become an important communication channel for brands. Brands create brand pages on social media to cultivate positive and strong relationships with consumers. This study seeks to enhance our understanding of how fashion brand pages in social media foster consumer-brand relationships by exploring the factors that affect the development of consumer-brand relationships. Drawing on the parasocial interaction theory, this study proposes parasocial interaction as a key factor of this process. Specifically, this study proposes four antecedents (vividness, interactivity, social presence, and focused attention) of consumers' parasocial interaction with brand pages, which further affects consumer responses in terms of affective engagement and brand loyalty. An online survey was administered with consumers who have followed and visited at least one fashion brand page via a social networking site (SNS). Structural equation modeling revealed that consumers' perceptions of vividness, interactivity, social presence, and focused attention on a fashion brand page positively affected their feelings towards parasocial interaction with the brand page, which in turn led to their affective engagement with the brand page and consequent brand loyalty. These findings suggest that consumers build relationships of varying degrees with brand pages in a similar manner to that with people, which leads to their development of a positive relationship with the brand. This study concludes with discussions and practical implications.

• International Journal of Knowledge Content Development & Technology
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• v.7 no.4
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• pp.5-26
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• 2017

A cross-cultural comparison of social networking structure on McDonald's Facebook fan sites between Taiwan and the USA was conducted utilizing the individualism/collectivism dimension proposed by Hofstede. Four network indicators are used to describe the network structure of McDonald's Facebook fan sites: size, density, clique and centralization. Individuals who post on both Facebook sites for the year of 2012 were considered as network participants for the purpose of the study. Due to the huge amount of data, only one thread of postings was sampled from each month of the year of 2012. The final data consists of 1002 postings written by 896 individuals and 5962 postings written by 5532 individuals from Taiwan and the USA respectively. The results indicated that the USA McDonald's Facebook fan network has more fans, while Taiwan's McDonald's Facebook fan network is more densely connected. Cliques did form among the overall multiplex and within the individual uniplex networks in two countries, yet no significant differences were found between them. All the fan networks in both countries are relatively centralized, mostly on the site operators.

• International Journal of Computer Science & Network Security
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• v.23 no.10
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• pp.97-106
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• 2023

Sentiment analysis using social network platforms such as Twitter has achieved tremendous results. Twitter is an online social networking site that contains a rich amount of data. The platform is known as an information channel corresponding to different sites and categories. Tweets are most often publicly accessible with very few limitations and security options available. Twitter also has powerful tools to enhance the utility of Twitter and a powerful search system to make publicly accessible the recently posted tweets by keyword. As popular social media, Twitter has the potential for interconnectivity of information, reviews, updates, and all of which is important to engage the targeted population. In this work, numerous methods that perform a classification of tweet sentiment in Twitter is discussed. There has been a lot of work in the field of sentiment analysis of Twitter data. This study provides a comprehensive analysis of the most standard and widely applicable techniques for opinion mining that are based on machine learning and lexicon-based along with their metrics. The proposed work is helpful to analyze the information in the tweets where opinions are highly unstructured, heterogeneous, and polarized positive, negative or neutral. In order to validate the performance of the proposed framework, an extensive series of experiments has been performed on the real world twitter dataset that alter to show the effectiveness of the proposed framework. This research effort also highlighted the recent challenges in the field of sentiment analysis along with the future scope of the proposed work.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2011.05a
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• pp.230-232
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• 2011

Owing to the advent of digital devices which equipped with GPS, such as smartphone and tablet pc, a number of LBSNS applications have been released and even SNS applications serve various Location-Based Services. In twitter's case, the news of interesting area is provided to user not by being subscribed them automatically, but by being searched on web-site. This paper describes the system designed for users want to subscribe the local news without procedure like searching using operators. This system uses PBSM(Partition Based Spatial-Merge Join) which has no index for batch processing and against a massive query. The results from Spatial Join are stored in Materialized View then provided to user.

• Journal of The Korean Digital Architecture Interior Association
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• v.7 no.2
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• pp.9-17
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• 2007

After 20th century, The using of data tend to important in a sphere of architecture. The recent European including MVRDV, Rem Koolhaas, Van Verkel and Zaha Hadid tend to the their own design strategy based on the objective data. This architectural design method leads to make new paradigm of contemporary architecture. For the purpose of the understanding a part of new architecture paradigm(datascping), I will analyze the relation of Thing system and Formation system in 36 works of MVRDV from 1992 to 2006. As a results are as follows. The purpose The results of this research are as follows: First, The physical and social elements(Thinking system) are density of site, networking, lighting & vista, micro-climate, energy, noise & vibration, life style, city, communication and variety. Second, The Formation system is layering & stacking, open & close, folding & extending and eco-friendly design. Finally, the major matrix of MVRDV's works is pragmatic and systematic approach to the lighting, climate and variety of community.

• Asia pacific journal of information systems
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• v.29 no.1
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• pp.35-49
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• 2019

The paper attempts to document the application of relevant Machine Learning (ML) models on Yelp (a crowd-sourced local business review and social networking site) dataset to analyze, predict and recommend business. Strategically using two cloud platforms to minimize the effort and time required for this project. Seven machine learning algorithms in Azure ML of which four algorithms are implemented in Databricks Spark ML. The analyzed Yelp business dataset contained 70 business attributes for more than 350,000 registered business. Additionally, review tips and likes from 500,000 users have been processed for the project. A Recommendation Model is built to provide Yelp users with recommendations for business categories based on their previous business ratings, as well as the business ratings of other users. Classification Model is implemented to predict the popularity of the business as defining the popular business to have stars greater than 3 and unpopular business to have stars less than 3. Text Analysis model is developed by comparing two algorithms, uni-gram feature extraction and n-feature extraction in Azure ML studio and logistic regression model in Spark. Comparative conclusions have been made related to efficiency of Spark ML and Azure ML for these models.

• The Journal of Society for e-Business Studies
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• v.16 no.1
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• pp.1-15
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• 2011

The new environment of music service has brought changes in digital music industry. Today, various forms of music contents are presented in ubiquitous environments. Thus, securing various contents becomes very important in monopolistic competition of music market. Under the circumstance, web 2.0 provides a networking environment to form diverse relations. Social Network Service (SNS) is a service to emphasize people relation and is different from information-centered Internet service. And mobile SNS becomes popular as Smartphone rapidly increases. NeowizBugs merged with NeowizInternet managing Sayclub of a music-specified SNS site. And the firm confirms comprehensive contents by making ties with SM entertainment. Thus, the integration corporation secures and manages a new business model by linking digital contents with SNS. Generally, music-specified SNS has advertisement business model and uses a recommend system utilizing the database of users. By introducing the case of NeowizBugs, this study tries to identify the success strategy of music distributors fitting ubiquitous environment including web 2.0, mobile SNS, Smartphone, etc.

• Journal of Internet Computing and Services
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• v.19 no.4
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• pp.123-133
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• 2018

This paper examined how the millennial generation consumes mobile news through social networking sites with regards to user patterns, preference topics and news values, and whether news topics and news values may influence their overall mobile SNS news consumption and interactivity. The findings show that more than 2/3 of respondents consumed mobile SNS news at least once everyday for 30minutes to one-hour. Male millennials tended to use Facebook and Kakao-talk more than female. While the portal site was the most accessed channel for consuming mobile news, SNS was the second, more than the combined use of national daily papers, TV, and internet newspapers. The respondents' demographic characteristics and news topics also affect the form and degree of news interactivity. With regards to their preferences and prioritization of news values, millennials tend to perceive 'impact' and 'usefulness' as being most important, despite the differences of their demographic characteristics. They also preferred those news values most. There were significant differences in terms of preferred news topics according to the demographics' characteristics.