• Asia pacific journal of information systems
• /
• v.18 no.2
• /
• pp.41-72
• /
• 2008

The purpose of this study is the investigation of the effects of user participation, network effect, social influence, and usefulness on stickiness and continued use on Internet communities. In this research, stickiness refers to repeat visit and visit duration to an Internet community. Continued use means the willingness to continue to use an Internet community in the future. Internet community-based companies can earn money through selling the digital contents such as game, music, and avatar, advertizing on internet site, or offering an affiliate marketing. For such money making, stickiness and continued use of Internet users is much more important than the number of Internet users. We tried to answer following three questions. Fist, what is the effects of user participation on stickiness and continued use on Internet communities? Second, by what is user participation formed? Third, are network effect, social influence, and usefulness that was significant at prior research about technology acceptance model(TAM) still significant on internet communities? In this study, user participation, network effect, social influence, and usefulness are independent variables, stickiness is mediating variable, and continued use is dependent variable. Among independent variables, we are focused on user participation. User participation means that Internet user participates in the development of Internet community site (called mini-hompy or blog in Korea). User participation was studied from 1970 to 1997 at the research area of information system. But since 1997 when Internet started to spread to the public, user participation has hardly been studied. Given the importance of user participation at the success of Internet-based companies, it is very meaningful to study the research topic of user participation. To test the proposed model, we used a data set generated from the survey. The survey instrument was designed on the basis of a comprehensive literature review and interviews of experts, and was refined through several rounds of pretests, revisions, and pilot tests. The respondents of survey were the undergraduates and the graduate students who mainly used Internet communities. Data analysis was conducted using 217 respondents(response rate, 97.7 percent). We used structural equation modeling(SEM) implemented in partial least square(PLS). We chose PLS for two reason. First, our model has formative constructs. PLS uses components-based algorithm and can estimated formative constructs. Second, PLS is more appropriate when the research model is in an early stage of development. A review of the literature suggests that empirical tests of user participation is still sparse. The test of model was executed in the order of three research questions. First user participation had the direct effects on stickiness(${\beta}$=0.150, p<0.01) and continued use (${\beta}$=0.119, p<0.05). And user participation, as a partial mediation model, had a indirect effect on continued use mediated through stickiness (${\beta}$=0.007, p<0.05). Second, optional participation and prosuming participation significantly formed user participation. Optional participation, with a path magnitude as high as 0.986 (p<0.001), is a key determinant for the strength of user participation. Third, Network effect (${\beta}$=0.236, p<0.001). social influence (${\beta}$=0.135, p<0.05), and usefulness (${\beta}$=0.343, p<0.001) had directly significant impacts on stickiness. But network effect and social influence, as a full mediation model, had both indirectly significant impacts on continued use mediated through stickiness (${\beta}$=0.11, p<0.001, and ${\beta}$=0.063, p<0.05, respectively). Compared with this result, usefulness, as a partial mediation model, had a direct impact on continued use and a indirect impact on continued use mediated through stickiness. This study has three contributions. First this is the first empirical study showing that user participation is the significant driver of continued use. The researchers of information system have hardly studies user participation since late 1990s. And the researchers of marketing have studied a few lately. Second, this study enhanced the understanding of user participation. Up to recently, user participation has been studied from the bipolar viewpoint of participation v.s non-participation. Also, even the study on participation has been studied from the point of limited optional participation. But, this study proved the existence of prosuming participation to design and produce products or services, besides optional participation. And this study empirically proved that optional participation and prosuming participation were the key determinant for user participation. Third, our study compliments traditional studies of TAM. According prior literature about of TAM, the constructs of network effect, social influence, and usefulness had effects on the technology adoption. This study proved that these constructs still are significant on Internet communities.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
• /
• v.11 no.2
• /
• pp.195-203
• /
• 2018

With the explosion of SNS(social network services) users, the social commerce market has emerged as a new consumer market, and will continue to grow in recent years. Despite the market environment, however, studies are lacking as to the causes of frustration that are hurting social commerce activation. This study is based on the 'Hezbollah' 2 Factor Theory and is a study of social commerce users' satisfaction and frustration factors. For this purpose, social commerce site characteristics and user characteristics were first derived from interviews and literature reviews to confirm their relationship to satisfaction and dissatisfied products. The results showed that the price discount rate, diversity, regional infrastructure, and e-commerce familiarity resulted in the impact on the definition of satisfaction, while the price discount rate, interoperability and innovation resulted in the definition of unsatisfactory goods. It also showed that satisfaction affects the definition of intended use. In particular, the price discount rate was found to be the only factor affecting the definition of unsatisfactory as well as affecting the definition of satisfaction.

• Journal of KIISE
• /
• v.44 no.4
• /
• pp.339-343
• /
• 2017

As the number of customers who write fake reviews is increasing, online shopping sites have difficulty in providing reliable reviews. Fake reviews are called review spam, and they are written to promote or defame the product. They directly affect sales volume of the product; therefore, it is important to detect review spam. Review spam detection methods suggested in prior researches were only based on an international site even though review spam is a widespread problem in domestic shopping sites. In this paper, we have presented new review features of the domestic shopping site NAVER, and we have applied the formerly introduced method to this site for performing an evaluation.

• Journal of Intelligence and Information Systems
• /
• v.20 no.2
• /
• pp.93-107
• /
• 2014

In this paper, we report what we have observed with regard to user-perspective issue clustering based on multi-layered two-mode network analysis. This work is significant in the context of data collection by companies about customer needs. Most companies have failed to uncover such needs for products or services properly in terms of demographic data such as age, income levels, and purchase history. Because of excessive reliance on limited internal data, most recommendation systems do not provide decision makers with appropriate business information for current business circumstances. However, part of the problem is the increasing regulation of personal data gathering and privacy. This makes demographic or transaction data collection more difficult, and is a significant hurdle for traditional recommendation approaches because these systems demand a great deal of personal data or transaction logs. Our motivation for presenting this paper to academia is our strong belief, and evidence, that most customers' requirements for products can be effectively and efficiently analyzed from unstructured textual data such as Internet news text. In order to derive users' requirements from textual data obtained online, the proposed approach in this paper attempts to construct double two-mode networks, such as a user-news network and news-issue network, and to integrate these into one quasi-network as the input for issue clustering. One of the contributions of this research is the development of a methodology utilizing enormous amounts of unstructured textual data for user-oriented issue clustering by leveraging existing text mining and social network analysis. In order to build multi-layered two-mode networks of news logs, we need some tools such as text mining and topic analysis. We used not only SAS Enterprise Miner 12.1, which provides a text miner module and cluster module for textual data analysis, but also NetMiner 4 for network visualization and analysis. Our approach for user-perspective issue clustering is composed of six main phases: crawling, topic analysis, access pattern analysis, network merging, network conversion, and clustering. In the first phase, we collect visit logs for news sites by crawler. After gathering unstructured news article data, the topic analysis phase extracts issues from each news article in order to build an article-news network. For simplicity, 100 topics are extracted from 13,652 articles. In the third phase, a user-article network is constructed with access patterns derived from web transaction logs. The double two-mode networks are then merged into a quasi-network of user-issue. Finally, in the user-oriented issue-clustering phase, we classify issues through structural equivalence, and compare these with the clustering results from statistical tools and network analysis. An experiment with a large dataset was performed to build a multi-layer two-mode network. After that, we compared the results of issue clustering from SAS with that of network analysis. The experimental dataset was from a web site ranking site, and the biggest portal site in Korea. The sample dataset contains 150 million transaction logs and 13,652 news articles of 5,000 panels over one year. User-article and article-issue networks are constructed and merged into a user-issue quasi-network using Netminer. Our issue-clustering results applied the Partitioning Around Medoids (PAM) algorithm and Multidimensional Scaling (MDS), and are consistent with the results from SAS clustering. In spite of extensive efforts to provide user information with recommendation systems, most projects are successful only when companies have sufficient data about users and transactions. Our proposed methodology, user-perspective issue clustering, can provide practical support to decision-making in companies because it enhances user-related data from unstructured textual data. To overcome the problem of insufficient data from traditional approaches, our methodology infers customers' real interests by utilizing web transaction logs. In addition, we suggest topic analysis and issue clustering as a practical means of issue identification.

• Journal of Industrial Technology
• /
• v.17
• /
• pp.43-50
• /
• 1997

Local administration is closely related with intention of residents. Especially, a plan item is closely related with life of residents. Therefore, it has to be logical and objective solution for opinion convergence. Decision of opinion has to be in a triangular position standard and stand in a trio of criteria in standard. But, opinion convergence of residents very difficult. Recently, the technique of GIS presents method for oponion convergence with logical and objective and scientifically solution. And, this study present method for decision of intention to a complex element with GRID and NETWORK techniques of GIS. This study present optimun site of constructure with the GIS technique in consideration of a side face of transportation, technical, social economy and environments.

• The Research Journal of the Costume Culture
• /
• v.27 no.6
• /
• pp.645-653
• /
• 2019

Laundry services are becoming more specialized and diversified. Therefore, this study investigated consumers' perceptions of professional laundry shops by analyzing social media data. For this purpose, text data from blogs, cafés, and Q&A sections ('Ji-Sik-In') on the portal site, naver.com, was collected. Sixty-four keywords were extracted from 2,213 social texts and transformed into a one-mode matrix using KrKwic, a program for the analysis of Korean text. Semantic network analysis was conducted to understand the network structure and the results were visualized using NodeXL. Keywords included fashion items and materials that require specialized professional laundry services, words related to the establishment of laundry shops, and laundry shop brands. Essential keywords of professional laundry shops included 'luxury,' 'footwear,' 'removal,' 'bag,' 'leather,' 'sneakers,' 'padding,' 'premium,' 'dyeing,' and 'franchise.' These results could be used to deduce that consumers perceive a professional laundry shop as a franchise shop offering specialized professional laundry services. A cluster analysis was conducted to identify the types of consumer perceptions of professional laundry shops. The network was divided into three groups: 'specialized professional laundry service,' 'laundry and repair of winter coats and jackets,' and 'the establishment of a professional laundry shop.' According to the results, consumers perceive professional laundry shops as franchises that offer specialized professional laundry services rather than general laundry services. Therefore, professional laundry shops need a strategy to develop special laundry services that differentiate them from other companies and communicate with consumers about these services.

• The Journal of Information Systems
• /
• v.21 no.2
• /
• pp.97-114
• /
• 2012

Given the rapid growth of social network services (SNS) such as Facebook and Cyworld, it is important to understand SNS users' decision-making processes such as purchasing and continuance intention. Especially, as a number of SNS providers such as Cyworld and Habbo Hotel recognize the sales of digital items as the main source of their profits, it is critical to in-depth understand SNS users' purchasing behaviors. In this regard, this study explores continued usage behaviors and purchase behaviors of digital items in an SNS environment using a longitudinal research method. This paper develops a theoretical model to deeply understand the key drivers of purchase behavior of digital items through constructs prescribed by two established research streams on information systems, namely continuance usage and habitual usage. Moreover, this study examines the effects of actual and ideal self-image congruity on SNS continuance intention and habit. The research model was tested by using survey data collected from 307 users who have experience with Cyworld. The analysis results show that SNS actual usage directly influence purchase behavior of digital items. SNS users' continuance intention and habit are key drivers to enhance the level of actual usage of the SNS. Both actual and ideal self-image congruity play a key role in enhancing continuance usage and habitual usage. The implication of research and discussions provides reference for SNS providers in marketing and IT strategy.

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

• Asia Marketing Journal
• /
• v.16 no.1
• /
• pp.117-132
• /
• 2014

This study examined the use of Facebook in United Arab Emirates. There were two objectives of this study. The first purpose was to identify the motive for the use of Facebook among people in U.A.E. This study conducted the survey using both qualitative and quantitative methods. One hundred eighty-three working people were used from the survey. Thirty-five questions identified from the interviews were used for the questionnaire design in quantitative method. Factor analysis showed six factors namely usefulness, usage, reliability, making new friends, ethical issue and openness of information. The total variance explained by all the factors was fifty-two percent. This study also examined the demographic variables whether they would play an important role in using the social network site. The study included two more variables, income and married status, which were not frequently examined by previous studies. MANOVA showed statistical significant differences (p < .01) across six factors. ANOVA results showed that gender variable affected only the factor of openness of information. Males were more likely to share their information compared to females. Income variable affected all the factors except the openness of information. The results showed that high-income people had the highest meanscores on three factors (usage, reliability, making new friends) while low-income people had the highest means on usefulness and ethical factors.Marital status had significant effects on usefulness, reliability, and ethical factors. Married people had the low scores on reliability and ethical factors. Lastly, education variable had no effect on all the factors examined.

• Journal of Families and Better Life
• /
• v.35 no.2
• /
• pp.1-16
• /
• 2017

The purpose of this study was to investigate adolescents' individual and microsystem variables including relationships with parents and friends affecting adolescents' experiences of mobile social networking site (SNS) cyberbullying based on the human ecological perspective. Data came from 344 middle school students who lived with both their parents in the Seoul and Gyunggi areas. A multiple regression analysis showed that adolescents' characteristics, relationships with parents, and friends were associated with their experiences of mobile SNS cyberbullying. These findings suggest that good relationships with parents could be protective factors for adolescents to reduce mobile SNS cyberbullying. However, adolescents' characteristics including aggression, depression, and delinquent peers were positively associated with adolescents' experiences of mobile SNS cyberbullying. This study highlights that various environments are closely related to adolescent development.