• Knowledge Management Research
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• v.13 no.2
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• pp.1-18
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• 2012

This article describes how attributes of social network contribute to enhance innovativeness of corporation which is considered to be one of the competitive factors in this global market. The study especially focused on employees' formal and informal communication that is expected to play a mediating role between the factors. 211 employees were randomly selected to participate in an online survey. The result has shown that the static correlation exists between social network, communication, and innovativeness. Closeness of social network was the only influencing factor on communication and innovativeness, and had a partial mediated effect between social network and innovativeness. Based on the suggested contribution for HRD intervention, various communication channels should be developed and supported in order to enhance innovation among social networks in organizations.

• Journal of Digital Convergence
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• v.10 no.1
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• pp.423-428
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• 2012

By shifting web2.0 users who share information from passive consumption and create their own information and exchange in the form of an active and visible appearance was changing. Most simply and easily with features that can be accessed. SNS is native to Korea me2day, Cyworld, (c) Logs and foreign SNS of Facebook, Twitter and a surge in user FramVille, Mafia War's Game, and many users use to SNG are. SNG's compared to the foreign national is active and not yet is a step. The domestic market, the benefits of this game online games and SNS in vogue these days to incorporate the concept in the market for a new form of the domestic game that the game, SNOG (Social Network Online Game, social networks, online games) to the expansion of flexible development direction, Expand accessibility, expansion of social skills is to present to the three.

• Journal of Korea Multimedia Society
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• v.19 no.2
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• pp.428-435
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• 2016

Hundreds of millions of new posts and information are being uploaded and propagated everyday on Online Social Networks(OSN) like Twitter, Facebook, or Instagram. This paper proposes and implements a GPS-location based SNS data mapping, analysis, and visualization system, called Smart SNS Map, which collects SNS data from Twitter and Instagram using hundreds of PlanetLab nodes distributed across the globe. Like no other previous systems, our system uniquely supports a variety of functions, including GPS-location based mapping of collected tweets and Instagram photos, keyword-based tweet or photo searching, real-time heat-map visualization of tweets and instagram photos, sentiment analysis, word cloud visualization, etc. Overall, a system like this, admittedly still in a prototype phase though, is expected to serve a role as a sort of social weather station sooner or later, which will help people understand what are happening around the SNS users, systems, society, and how they feel about them, as well as how they change over time and/or space.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.3
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• pp.1168-1188
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• 2018

Social Network Aggregators are used to maintain and manage manifold accounts over multiple online social networks. Displaying the Activity feed for each social network on a common dashboard has been the status quo of social aggregators for long, however retrieving the desired data from various social networks is a major concern. A user inputs the query desiring the specific outcome from the social networks. Since the intention of the query is solely known by user, therefore the output of the query may not be as per user's expectation unless the system considers 'user-centric' factors. Moreover, the quality of solution depends on these user-centric factors, the user inclination and the nature of the network as well. Thus, there is a need for a system that understands the user's intent serving structured objects. Further, choosing the best execution and optimal ranking functions is also a high priority concern. The current work finds motivation from the above requirements and thus proposes the design of a query processing system to retrieve information from social network that extracts user's intent from various social networks. For further improvements in the research the machine learning techniques are incorporated such as Latent Dirichlet Algorithm (LDA) and Ranking Algorithm to improve the query results and fetch the information using data mining techniques.The proposed framework uniquely contributes a user-centric query retrieval model based on natural language and it is worth mentioning that the proposed framework is efficient when compared on temporal metrics. The proposed Query Processing System to Retrieve Information from Social Network (QPSSN) will increase the discoverability of the user, helps the businesses to collaboratively execute promotions, determine new networks and people. It is an innovative approach to investigate the new aspects of social network. The proposed model offers a significant breakthrough scoring up to precision and recall respectively.

• Journal of the Korean Operations Research and Management Science Society
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• v.34 no.3
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• pp.1-27
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• 2009

Since online knowledge networks usually consist of a larger, loosely knit, and geographically distributed group of "strangers" who may not know each other very well, members may not willingly share their knowledge with others. In order to address this challenge, this study looks Into the factors that are expected to affect knowledge sharing in an online knowledge network. For empirical validation, we choose "the global network of Korean scientists and engineers (KOSEN)" as one of the best practices of online knowledge networks. By using the archival, network, and survey data, we validate two models of knowledge sharing in sequence (i.e., knowledge contribution and knowledge utilization models) and then discuss the results. The findings of this study show that individuals not only contribute but also utilize knowledge in an online knowledge network when they are structurally embedded and perceive a strong reciprocity. In the network. In addition, taking pleasure in helping is found to positively affect knowledge contribution, whereas perceiving usefulness is found to Influence knowledge utilization. Contributions of this study and future research opportunities are also discussed.

• International Journal of Computer Science & Network Security
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• v.23 no.8
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• pp.101-106
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• 2023

In this busy world actually stress is continuously grow up in research and monitoring social websites. The social interaction is a process by which people act and react in relation with each other like play, fight, dance we can find social interactions. In this we find social structure means maintain the relationships among peoples and group of peoples. Its a limit and depends on its behavior. Because relationships established on expectations of every one involve depending on social network. There is lot of difference between emotional pain and physical pain. When you feel stress on physical body we all feel with tensions, stress on physical consequences, physical effects on our health. When we work on social network websites, developments or any research related information retrieving etc. our brain is going into stress. Actually by social network interactions like watching movies, online shopping, online marketing, online business here we observe sentiment analysis of movie reviews and feedback of customers either positive/negative. In movies there we can observe peoples reaction with each other it depends on actions in film like fights, dances, dialogues, content. Here we can analysis of stress on brain different actions of movie reviews. All these movie review analysis and stress on brain can calculated by machine learning techniques. Actually in target oriented business, the persons who are working in marketing always their brain in stress condition their emotional conditions are different at different times. In this paper how does brain deal with stress management. In software industries when developers are work at home, connected with clients in online work they gone under stress. And their emotional levels and stress levels always changes regarding work communication. In this paper we represent emotional intelligence with stress based analysis using machine learning techniques in social networks. It is ability of the person to be aware on your own emotions or feeling as well as feelings or emotions of the others use this awareness to manage self and your relationships. social interactions is not only about you its about every one can interacting and their expectations too. It about maintaining performance. Performance is sociological understanding how people can interact and a key to know analysis of social interactions. It is always to maintain successful interactions and inline expectations. That is to satisfy the audience. So people careful to control all of these and maintain impression management.

• Journal of information and communication convergence engineering
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• v.9 no.1
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• pp.1-5
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• 2011

Everyday, technology is evolved in many different disciplines. Computer and smart devices revolution take part of the evolved technology that continuously promising new features. Moreover, social networks services recently become widely popular, which most people in the world become a social-network-fond. In addition to the revolution of the evolved technology and social networks services, ubiquitousness is taking significant part in our daily lives. Although, there are many e-learning systems already existed, which use Internet technology along with a Web technology to provide education in various ways, in despite of that, there is no such existing system exploits the usefulness of smart devices along with the legacy of the online social networks besides the power of the ubiquitous computing technology. Therefore, we propose a smart device application, which fills the gap that has been missing in the recent contemporary era. It is an application that runs on smart devices particularly Smartphone devices; we call our system “Smart Device based Social E-learning System(SDES)”. We have preliminary implemented our system on Android OS. In this paper, we intentionally propose the system in order to ease the way people learn, to provide interactive accessibility in our system, and to utilize the advanced technology more wisely.

• Journal of Information Processing Systems
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• v.17 no.1
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• pp.163-177
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• 2021

Many methods of discovering social networking communities or clustering of features are based on the network structure or the content network. This paper proposes a community discovery method based on topic models using a time factor and an unsupervised clustering method. Online community discovery enables organizations and businesses to thoroughly understand the trend in users' interests in their products and services. In addition, an insight into customer experience on social networks is a tremendous competitive advantage in this era of ecommerce and Internet development. The objective of this work is to find clusters (communities) such that each cluster's nodes contain topics and individuals having similarities in the attribute space. In terms of social media analytics, the method seeks communities whose members have similar features. The method is experimented with and evaluated using a Vietnamese corpus of comments and messages collected on social networks and ecommerce sites in various sectors from 2016 to 2019. The experimental results demonstrate the effectiveness of the proposed method over other methods.

• Knowledge Management Research
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• v.14 no.1
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• pp.21-37
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• 2013

Due to the development of social networks and smartphones, many different kinds of issues have emerged in business and society. By reflecting these trends, social network sites have appeared and they are recognized as the new concept of sites. The major feature of the social network sites is that the social relationship had been taken to the online space. Social network sites support the formation of a network and offer users the relationship between users offline as well as online. Based on the features mentioned above, users enjoy the benefits using social network sites. These social network sites in the enterprise can be used to form relationships with customers. This study identified the influencing factors as relational benefits and social influence on relationship commitment in social network sites. In addition, we analyzed that how the relationship commitment between users affects user loyalty after their using social network sites. We presented empirical results by utilizing structural equation model with 244 respondents and the significant implications for the academy and the practice with discussions.

• The Research Journal of the Costume Culture
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• v.25 no.6
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• pp.928-942
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• 2017

Social media has become an integral part of consumers' daily lives. Individuals connect with one another on social networking sites to like, share, and post information and experiences. As social media become popular among millennials, a growing number of fashion retailers use social media networks in the context of online commerce transactions. Accordingly, an increased number of fashion retailers has been using social media as an advertising tool and a retail channel. Despite the popularity of social media among millennials, empirical findings are limited to reveal factors associated with young consumers' intentions to use social commerce in fashion shopping. This study sought to examine factors affecting millennials' intentions to use social commerce in fashion shopping by adopting the technology acceptance model. A total of 524 college students completed an online survey in the U.S. The results of structural equation model confirmed that perceived ease of use, usefulness, and enjoyment had a positive impact on millennials' attitudes and intentions toward fashion shopping in social commerce. While both perceived ease of use and usefulness positively influenced enjoyment, usefulness had a stronger impact than ease of use. Compared to usefulness, enjoyment had much stronger impact on attitudes. Further structural model analysis revealed a direct, positive influence of perceived usefulness of social commerce on perceived enjoyment of social commerce, which has not been explored in prior studies. These findings provide theoretical and managerial implications.