• Journal of Service Research and Studies
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• v.5 no.1
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• pp.79-89
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• 2015

Recently, with the introduction of social network services, studies that try to make use of them for the various purposes have been actively investigated. In order to proceed with the research that takes advantage of social network services, it is necessary to review the relevant literature and to identify trends in researches. However, the researches of social network are massive amount, so to review the huge amount of relevant research literature is a very difficult task. Therefore, in this study, we analyze systematically the tendency of research related to social network service focusing on Twitter. Especially, we use the SLR (Systematic Literature Review) technique for systematic literature survey and analysis. For the literature survey, we select korean literature resource sites and 243 studies of literature that are surveyed. Studies and analyzes on Twitter in a variety of research studies were also using Twitter data that way beyond the simple question directly.

• Informatization Policy
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• v.18 no.3
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• pp.25-49
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• 2011

As a way to gather diverse information required for everyday living, the importance of social networks has been growing. Social network services have been spreading rapidly because of diffusion of the Internet, evolution of social network sites, and recognition of the importance of social networks. Recently, the social network service has been evolved based on a new paradigm, Web 2.0, pursuing participation and openness. Following the adoption of Web 2.0 technologies, the social network service allows users to make and maintain new relationships in a more convenient way. Users of the social network service tend to reveal their personal information, and share their ideas and content with other people; in the process they become aware of their existence, feel satisfaction with life and exert influence to others as a member of the society. This study uses higher order factor analysis to analyze factors that affect the intention of using the social network service. A research model was developed with second-order factors including perceived social presence, perceived gratification and perceived social influence. First-order factors are grouped by technical, individual and social factors. Smart PLS 2.0 was used to conduct empirical analysis. The analysis results supported the validity of the research model.

• The Journal of Information Systems
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• v.29 no.2
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• pp.221-242
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• 2020

Purpose This study collects data of the recently activated online black market and analyzes it to present a specific method for preparing for a hacking attack. This study aims to make safe from the cyber attacks, including hacking, from the perspective of individuals and businesses by closely analyzing hacking methods and tools in a situation where they are easily shared. Design/methodology/approach To prepare for the hacking attack through the online black market, this study uses the routine activity theory to identify the opportunity factors of the hacking attack. Based on this, text mining and social network techniques are applied to reveal the most dangerous areas of security. It finds out suitable targets in routine activity theory through text mining techniques and motivated offenders through social network analysis. Lastly, the absence of guardians and the parts required by guardians are extracted using both analysis techniques simultaneously. Findings As a result of text mining, there was a large supply of hacking gift cards, and the demand to attack sites such as Amazon and Netflix was very high. In addition, interest in accounts and combos was in high demand and supply. As a result of social network analysis, users who actively share hacking information and tools can be identified. When these two analyzes were synthesized, it was found that specialized managers are required in the areas of proxy, maker and many managers are required for the buyer network, and skilled managers are required for the seller network.

• International Journal of Advanced Culture Technology
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• v.11 no.3
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• pp.332-337
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• 2023

The purpose of the study was to analyze consumers' perceptions of gamification. Based on the analyzed data, we would like to provide data by systematically organizing the concept, game elements, and mechanisms of gamification. Recently, gamification can be easily found around medical care, corporate marketing, and education. This study collected keywords from social media portal sites Naver, Daum, and Google from 2018 to 2023 using TEXTOM, a social media analysis tool. In this study, data were analyzed using text mining, semantic network analysis, and CONCOR analysis methods. Based on the collected data, we looked at the relevance and clusters related to gamification. The clusters were divided into a total of four clusters: 'Awareness of Gamification', 'Gamification Program', 'Future Technology of Gamification', and 'Use of Gamification'. Through social media analysis, we want to investigate and identify consumers' perceptions of gamification use, and check market and consumer perceptions to make up for the shortcomings. Through this, we intend to develop a plan to utilize gamification.

• The Journal of Information Systems
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• v.23 no.1
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• pp.1-28
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• 2014

소셜 네트워크 서비스의 확산과 더불어 소셜 네트워크 게임(이하에서는 소셜게임이라 함)이 부각되고 있다. 한편, 소셜게임이 인기를 끌면서 소셜 네트워크 서비스가 더욱 확산되는 계기가 되기도 한다. 사용자들을 소셜게임에 몰입하도록 유인하는 요인이 무엇인가를 파악하면 소셜 네트워크 서비스가 더욱 발전할 수 있는 방안을 찾을 수 있다. 따라서 본 연구는 사용자들을 소셜게임에 몰입하도록 유인하는 요인이 무엇인가를 분석하는데 있다. 본 연구에서는 대표적인 소셜 네트워크 사이트라 할 수 있는 페이스북의 소셜게임 사용자들을 대상으로 설문조사를 실시하였다. 280명의 사용자들을 대상으로 한 설문을 통해, 소셜게임에의 몰입, 게임스토리, 게임그래픽, 게임사회화, 게임 통제력, 게임 사용용이성의 관계를 구조방정식모형으로 분석하였다. 특히, 게임 사회화와 게임그래픽은 몰입에 직접적으로 영향을 주기도 하며 게임 사용용이성을 통해 간접적으로도 영향을 주었다. 한편, 게임스토리는 몰입에 직접적으로만 영향을 주고, 게임 통제력을 게임사용 용이성을 통해 간접적으로 영향을 준다. 본 연구는 몰입이론과 기술수용이론을 토대로 하고 있지만, 소셜게임에서의 몰입에 대한 최초의 연구이기 때문에 후속 연구에 지침이 될 수 있다. 또한 소셜게임을 개발하는 사업자들이 무엇에 역점을 두고 게임을 개발하고 서비스해야 할 것인가에 대한 지침이 될 수 있다.

• Journal of Contemporary Eastern Asia
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• v.17 no.2
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• pp.147-175
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• 2018

Under authoritarian regimes, citizen-led NGOs such as environmental NGOs (ENGOs) often operate under close scrutiny of the government. While this presents a challenge to a single ENGO, we propose here - in line with existing research on network effects - that there are opportunities for multiple ENGOs to coordinate and thus work in ways that supersede government controls, affect public opinion, and contribute to policy revision and/or creation. In this paper, we specifically examine the possibility that the gamut of citizen-based ENGOs in China are coordinating. Based on network analysis of ENGOs web pages as well as interviews with more than a dozen ENGO leaders between 2014 and 2016, we find that ENGOs have few direct and public connections to each other, but social media sites and personal connections offline provide a crucial function in creating bridges. A closer examination of these bridges reveals, however, that they can be substantive to the environmental discussion or functional to the dissemination of web page information but typically not both. In short, ENGOs in China are not directly connected but rather are connected in a way that responds to the available social media and the government's censorship practices.

• International Journal of Computer Science & Network Security
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• v.21 no.8
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• pp.238-246
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• 2021

The rapid rise of the Internet and social media has resulted in a large number of text-based reviews being placed on sites such as social media. In the age of social media, utilizing machine learning technologies to analyze the emotional context of comments aids in the understanding of QoS for any product or service. The classification and analysis of user reviews aids in the improvement of QoS. (Quality of Services). Machine Learning algorithms have evolved into a powerful tool for analyzing user sentiment. Unlike traditional categorization models, which are based on a set of rules. In sentiment categorization, Bidirectional Long Short-Term Memory (BiLSTM) has shown significant results, and Convolution Neural Network (CNN) has shown promising results. Using convolutions and pooling layers, CNN can successfully extract local information. BiLSTM uses dual LSTM orientations to increase the amount of background knowledge available to deep learning models. The suggested hybrid model combines the benefits of these two deep learning-based algorithms. The data source for analysis and classification was user reviews of Indian Railway Services on Twitter. The suggested hybrid model uses the Keras Embedding technique as an input source. The suggested model takes in data and generates lower-dimensional characteristics that result in a categorization result. The suggested hybrid model's performance was compared using Keras and Word2Vec, and the proposed model showed a significant improvement in response with an accuracy of 95.19 percent.

• International Journal of Computer Science & Network Security
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• v.21 no.3
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• pp.206-211
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• 2021

Internet users are increasingly invited to express their opinions on various subjects in social networks, e-commerce sites, news sites, forums, etc. Much of this information, which describes feelings, becomes the subject of study in several areas of research such as: "Sensing opinions and analyzing feelings". It is the process of identifying the polarity of the feelings held in the opinions found in the interactions of Internet users on the web and classifying them as positive, negative, or neutral. In this article, we suggest the implementation of a sentiment analysis tool that has the role of detecting the polarity of opinions from people about COVID-19 extracted from social media (tweeter) in the Arabic language and to know the impact of the pre-processing phase on the opinions classification. The results show gaps in this area of research, first of all, the lack of resources when collecting data. Second, Arabic language is more complexes in pre-processing step, especially the dialects in the pre-treatment phase. But ultimately the results obtained are promising.

• Asia pacific journal of information systems
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• v.30 no.2
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• pp.284-307
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• 2020

Customer engagement has been the main objective of brand companies in their marketing through social networking sites (SNS). Facebook is the most popular platform for SNS marketing, especially for companies that try to engage with their customers by providing various values through their brand pages (i.e., brand communities). The management of brand pages, therefore, becomes "the means" by which to achieve the result ("the end") of SNS marketing, and visitors to the brand pages (i.e., brand communities) then come to have a favorable attitude toward the brand. Based on a "means-ends" framework, this study examines the development of engagement between customers and brands in terms of brand page engagement as the means objective and brand attitude as the ends objective in the context of Facebook. This study further examines the antecedents and consequences of brand page engagement based on the customer value theory with two-stage data collection. This study contributes to the literature by explaining the roles and effects of brand page engagement in SNS marketing. This study further provides guidance to SNS providers and practitioners on SNS marketing strategies.

• Knowledge Management Research
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• v.24 no.2
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• pp.161-183
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• 2023

Social Q&A sites, where individuals freely ask and answer each other online, play an important role as a public knowledge repository. For their sustainable growth, social Q&A sites constantly need new askers and new answerers. However, previous studies have focused only on answerers, with little attention to new users or askers. This study examines the factors encouraging new users to continue using social Q&A sites based on motivational affordance theory and self-determination theory, and also investigates whether the factors differ depending on the types of users (i.e., new asker vs. new answerer). In addition, the moderating effect of prior experience with a member Q&A site was examined. Using logistic regression and XGBoost, we analyzed online activity data from 25,000 users in the Stack Exchange Network and found that design elements with motivational affordances had significant impacts on new users' continuance behavior. The experience of a member Q&A site negatively moderated the influence of the antecedents of continuance behavior. Interestingly, the influence of editing was not significant in the analysis of new users as a whole, but was significant in the separate analyses of askers (significantly negative) and answerers (significantly positive).