• Journal of Internet Computing and Services
• /
• v.15 no.1
• /
• pp.73-88
• /
• 2014

Online communities are getting more popular with the development of information technology. It is essential that community members participate actively and share their contents or opinions continuously for the success and growth of online communities. However, it is revealed that most of members just take the role of passive observer. They are lurking community information and contents without any contribution. In this sense, this study focuses on explore lurking behavior of online community members. This study investigates the effect of the characteristics of online community, community members, and personal traits on user's lurking intention. Member familiarity and community identity have a strong positive effect on de-lurking intention, while the perception of usefulness and ease of use for communities and member expertise have a negative effect on de-lurking intention. Interestingly, users with a low level of self-esteem have higher level of motivation of participation than those with a high level of self-esteem. Finally, this study proposes several strategies to enhance information and contents sharing in online communities.

• The Journal of the Korea Contents Association
• /
• v.21 no.1
• /
• pp.24-38
• /
• 2021

This study aims to measure Korea's global competitiveness in intelligent information technology, which is the core technology of the 4th industrial revolution. For analysis, we collect patents of each field and prior patents cited by them, which are applied at the U.S. Patent Office (USPTO) between 2010 and 2018 from PATSTAT Online. A global knowledge transfer network was established by grouping citing- and cited-relationships at a national level. The in-degree centrality is used to evaluate technology acceptance, which indicates the process of absorbing existing technological knowledge to create new knowledge in each field. Second, to evaluate the impact of existing technological knowledge on the creation of new one, the out-degree centrality is investigated. Third, we apply the PageRank algorithm to qualitatively and quantitatively investigate the importance of the relationships between countries. As a result, it is confirmed through all the indicators that the AI sector is currently the least competitive.

• International Journal of Computer Science & Network Security
• /
• v.23 no.1
• /
• pp.112-119
• /
• 2023

Traditionally used for networking computers and communications, the Internet has been evolving from the beginning. Internet is the backbone for many things on the web including social media. The concept of social networking which started in the early 1990s has also been growing with the internet. Social Networking Sites (SNSs) sprung and stayed back to an important element of internet usage mainly due to the services or provisions they allow on the web. Twitter and Facebook have become the primary means by which most individuals keep in touch with others and carry on substantive conversations. These sites allow the posting of photos, videos and support audio and video storage on the sites which can be shared amongst users. Although an attractive option, these provisions have also culminated in issues for these sites like posting offensive material. Though not always, users of SNSs have their share in promoting hate by their words or speeches which is difficult to be curtailed after being uploaded in the media. Hence, this article outlines a process for extracting user reviews from the Twitter corpus in order to identify instances of hate speech. Through the use of MPCA (Modified Principal Component Analysis) and ECNN, we are able to identify instances of hate speech in the text (Enhanced Convolutional Neural Network). With the use of NLP, a fully autonomous system for assessing syntax and meaning can be established (NLP). There is a strong emphasis on pre-processing, feature extraction, and classification. Cleansing the text by removing extra spaces, punctuation, and stop words is what normalization is all about. In the process of extracting features, these features that have already been processed are used. During the feature extraction process, the MPCA algorithm is used. It takes a set of related features and pulls out the ones that tell us the most about the dataset we give itThe proposed categorization method is then put forth as a means of detecting instances of hate speech or abusive language. It is argued that ECNN is superior to other methods for identifying hateful content online. It can take in massive amounts of data and quickly return accurate results, especially for larger datasets. As a result, the proposed MPCA+ECNN algorithm improves not only the F-measure values, but also the accuracy, precision, and recall.

• Informatization Policy
• /
• v.28 no.3
• /
• pp.23-48
• /
• 2021

ICT technology development has led to a breakthrough change in government decision making by improving mutual communication between various stakeholders. The formation of ICT-based cooperation network between public organizations and civic tech developers to solve the problem of masks in the COVID-19 pandemic serves as a milestone. The purpose of this study is to examine the properties of e-Governance and analyze the dynamic network structure of the communication process for chat rooms created during the development of public mask apps. First, as a result of the analysis, the possibility of online-based e-Governance can be identified. In addition, the combination of expertise to solve social problems interacted organically within the network. Emotional communication for cooperation between key actors was marked as important for the successful operation of the network.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.16 no.2
• /
• pp.1016-1025
• /
• 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 People, Plants, and Environment
• /
• v.22 no.5
• /
• pp.455-466
• /
• 2019

This study was carried out to analyze trends in floral products and services through the big data analysis of various social networking services (SNSs) and then to provide objective marketing directions for the floricultural industry. To analyze the big data of SNSs, we used four analytical methods: Cotton Trend (Social Matrix), Naver Big Data Lab, Instagram Big Data Analysis, and YouTube Big Data Analysis. The results of the big data analysis showed that SNS users paid positive attention to flower one-day classes that can satisfy their needs for direct experiences. Consumers of floral products and services had their favorite designs in mind and purchased floral products very actively. The demand for flower items such as bouquets, wreaths, flower baskets, large bouquets, orchids, flower boxes, wedding bouquets, and potted plants was very high, and cut flowers such as roses, tulips, and freesia were most popular as of June 1, 2019. By gender of consumers, females (68%) purchased more flower products through SNSs than males (32%). Consumers preferred mobile devices (90%) for online access compared to personal computers (PCs; 10%) and frequently searched flower-related words from February to May for the past three years from 2016 to 2018. In the aspect of design, they preferred natural style to formal style. In conclusion, future marketing activities in the floricultural industry need to be focused on social networks based on the results of big data analysis of popular SNSs. Florists need to provide consumers with the floricultural products and services that meet the trends and to blend them with their own sensitivity. It is also needed to select SNS media suitable for each gender and age group and to apply effective marketing methods to each target.

• Journal of Intelligence and Information Systems
• /
• v.21 no.3
• /
• pp.19-36
• /
• 2015

Social media is an emerging issue in content services and in current business environment. YouTube is the most representative social media service in the world. YouTube is different from other conventional content services in its open user participation and contents creation methods. To promote a content in YouTube, it is important to understand the diffusion phenomena of contents and the network structural characteristics. Most previous studies analyzed impact factors of contents diffusion from the view point of general behavioral factors. Currently some researchers use network structure factors. However, these two approaches have been used separately. However this study tries to analyze the general impact factors on the view count and content based network structures all together. In addition, when building a content based network, this study forms the network structure by analyzing user comments on 22,370 contents of YouTube not based on the individual user based network. From this study, we re-proved statistically the causal relations between view count and not only general factors but also network factors. Moreover by analyzing this integrated research model, we found that these factors affect the view count of YouTube according to the following order; Uploader Followers, Video Age, Betweenness Centrality, Comments, Closeness Centrality, Clustering Coefficient and Rating. However Degree Centrality and Eigenvector Centrality affect the view count negatively. From this research some strategic points for the utilizing of contents diffusion are as followings. First, it is needed to manage general factors such as the number of uploader followers or subscribers, the video age, the number of comments, average rating points, and etc. The impact of average rating points is not so much important as we thought before. However, it is needed to increase the number of uploader followers strategically and sustain the contents in the service as long as possible. Second, we need to pay attention to the impacts of betweenness centrality and closeness centrality among other network factors. Users seems to search the related subject or similar contents after watching a content. It is needed to shorten the distance between other popular contents in the service. Namely, this study showed that it is beneficial for increasing view counts by decreasing the number of search attempts and increasing similarity with many other contents. This is consistent with the result of the clustering coefficient impact analysis. Third, it is important to notice the negative impact of degree centrality and eigenvector centrality on the view count. If the number of connections with other contents is too much increased it means there are many similar contents and eventually it might distribute the view counts. Moreover, too high eigenvector centrality means that there are connections with popular contents around the content, and it might lose the view count because of the impact of the popular contents. It would be better to avoid connections with too powerful popular contents. From this study we analyzed the phenomenon and verified diffusion factors of Youtube contents by using an integrated model consisting of general factors and network structure factors. From the viewpoints of social contribution, this study might provide useful information to music or movie industry or other contents vendors for their effective contents services. This research provides basic schemes that can be applied strategically in online contents marketing. One of the limitations of this study is that this study formed a contents based network for the network structure analysis. It might be an indirect method to see the content network structure. We can use more various methods to establish direct content network. Further researches include more detailed researches like an analysis according to the types of contents or domains or characteristics of the contents or users, and etc.

• The Journal of the Korea Contents Association
• /
• v.20 no.12
• /
• pp.36-48
• /
• 2020

App market has continuously been growth since its launch. The market revenues will reach about 1,000 billion US dollars in 2019. App is a core service for smartphone. Currently, there are more than 1.5 million mobile apps in App platform calling out for attention. So, if you are looking at developing a successful app, you need to have a solid marketing and distribution strategy. Online word of mouth(eWOM) is one of the most effective, powerful App marketing method. eWOM affect potential consumers' decision making, and this effect can spread rapidly through online social network. Despite the increasing research on word of mouth, only few studies have focused on content analysis. Most of studies focused on the causes and acceptance of eWOM and eWOM performance measurement. This study aims to content analysis of mobile apps review In 2013, Google researchers announced Word2Vec. This method has overcome the weakness of previous studies. This is faster and more accurate than traditional methods. This study found out the relationship between mobile app reviews and checked for reactions by Word2vec.

• East Asian Journal of Business Economics (EAJBE)
• /
• v.6 no.3
• /
• pp.37-47
• /
• 2018

Purpose - This paper investigates the major determinants of consumer decision making for smartphone's consumers in a developing country in Africa especially in Gabon. Analysis of Perceived Quality, Perceived Price, Perceived Risk, Brand Image, Perceived Value, and Purchase Intention Research design and methodology - In order to proceed the empirical research, online survey was done via email and social media network and data was collected from 289 random respondents. Therefore, to assess the reliability, the validity and test hypothesis Statistical Package for Social Sciences (SPSS) version 21 was used. Results - After data collection and analysis, results have proved that brand image, perceived price does influence perceived quality, and perceived quality negatively influence perceived risk. The results also show perceived risk along with brand image, perceived price and quality could not influence perceived value. The findings also indicate that perceived value slightly influence purchase intentions. Conclusions - The results of the study show that it is essential to develop an understanding of value in the purchasing process. This study should also provide a glimpse to both marketers and manufacturers about consumers' perceptions towards smartphones.

• Journal of Digital Contents Society
• /
• v.9 no.2
• /
• pp.317-323
• /
• 2008

The purpose of this study is to show typology of virtual world and to look out how virtual world develops especially in Korea. As paradigm changes, the scientific virtual reality and world wide web are absorbed into 3-D virtual world in Metaverse. The metaverse is the convergence of virtually enhanced physical reality and physically persistent virtual space. There are two categories of virtual world, the Ludic Virtual World which is oriented from games like MMORPGs and the Social Virtual World which is oriented from network communication system. Compared to North America and Europe, the Ludic Virtual World and game society grow and develop quickly in Korea. It's because Korean users prefer the online environment where millions of people live out a collective fantasy existence.