• Journal of Internet Computing and Services
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• v.18 no.1
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• pp.89-103
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• 2017

This paper analyzed the influence of government-owned social media's environmental characteristics on the level of users' active participation and types of message diffusion during government's crisis. The social media environment was categorized based on human interactivity and media interactivity. Users' active participation was measured based on amount of like/dislike and number of comments. User's comments were categorized through network analysis. This study found that the level of user's active participation was high on the information-provider participation type and the relationship-oriented participation type. The level of user's active participation was low on the information-provider type and the limited platform. The analysis of message diffusion type showed that a restrictive rational opinion type was found for the limited platform and diffusive or restrictive emotional opinion types were found for other types of social media environment. This study found that during MERS crisis, the government did not provide messages suitable for the social media environment, and the media environment influenced users' participation and comments. The government should provide user friendly social media environment by increasing interaction with users and should make efforts to communicate with users in crisis situation.

• International Journal of Computer Science & Network Security
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• v.21 no.7
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• pp.70-76
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• 2021

The relevance of intelligence involves the definition of such communication systems of PR-management and branding of media channels with the use of social networks, which are already implemented in practice by modern representatives of professional PR product. The purpose of the investigation is to determine the system of implementation of technologies of PR-management and branding of media channels with the use of social networks based on a survey of PR and brand of different media channels on the basis of a survey of brand managers and PR. 980 respondents from Ukraine took part in the survey. The survey was conducted on the Google-forms platform. The results outline a list of the most popular social networks and messengers for the implementation of PR management and branding technologies, including Facebook, Twitter, Google, LinkedIn, Tumblr; Telegram, WhatsApp, Viber, Skype. It is determined that the criteria of branding analysis are informativeness, centralization/distribution, content, feedback intensity. Identified 2 prospects for the development of branding in an interactive media environment (creation of a presentation system; integration of websites of social media and companies in universal centers). The criteria of general importance of the factors influencing the behavioral intention of consumers to use social media channels are presented (satisfaction, accessibility, perceived usefulness, trust, ease of use, attitude, social influence, self-efficacy). The meaning of the content of social media channels (public, informational and communication) is indicated. The practical significance of the study was to present the links between the criteria, development prospects and the values of branding factors.

• Journal of Information Science Theory and Practice
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• v.12 no.1
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• pp.39-59
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• 2024

An online social network is a platform that is continuously expanding, which enables groups of people to share their views and communicate with one another using the Internet. The social relations among members of the public are significantly improved because of this gesture. Despite these advantages and opportunities, criminals are continuing to broaden their attempts to exploit people by making use of techniques and approaches designed to undermine and exploit their victims for criminal activities. The field of digital forensics, on the other hand, has made significant progress in reducing the impact of this risk. Even though most of these digital forensic investigation techniques are carried out manually, most of these methods are not usually appropriate for use with online social networks due to their complexity, growth in data volumes, and technical issues that are present in these environments. In both civil and criminal cases, including sexual harassment, intellectual property theft, cyberstalking, online terrorism, and cyberbullying, forensic investigations on social media platforms have become more crucial. This study explores the use of machine learning techniques for addressing criminal incidents on social media platforms, particularly during forensic investigations. In addition, it outlines some of the difficulties encountered by forensic investigators while investigating crimes on social networking sites.

• Proceedings of the Korea Information Processing Society Conference
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• 2017.04a
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• pp.661-664
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• 2017

Recently, during disasters occurrence, dealing with emergencies has been handled well by the early transmission of disaster relating notifications on social media networks (e.g., Twitter or Facebook). Intuitively, with their characteristics (e.g., real-time, mobility) and big communities whose users could be regarded as volunteers, social networks are proved to be a crucial role for disasters response. However, the amount of data transmitted during disasters is an obstacle for filtering informative messages; because the messages are diversity, large and very noise. This large volume of data could be seen as Social Big Data (SBD). In this paper, we proposed a big data platform for collecting and analyzing disasters' data from SBD. Firstly, we designed a collecting module; which could rapidly extract disasters' information from the Twitter; by big data frameworks supporting streaming data on distributed system; such as Kafka and Spark. Secondly, we developed an analyzing module which learned from SBD to distinguish the useful information from the irrelevant one. Finally, we also designed a real-time visualization on the web interface for displaying the results of analysis phase. To show the viability of our platform, we conducted experiments of the collecting and analyzing phases in 10 days for both real-time and historical tweets, which were about disasters happened in South Korea. The results prove that our big data platform could be applied to disaster information based systems, by providing a huge relevant data; which can be used for inferring affected regions and victims in disaster situations, from 21.000 collected tweets.

• International Journal of Internet, Broadcasting and Communication
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• v.9 no.3
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• pp.59-69
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• 2017

The best 'hub' to communicate with the citizen is using social media to marketing the business. However, there has several issued and the most common issue that face in critical is a capital issue. This issue is always highlight because most of automatic sentiment detection tool for Facebook or any other social media price is expensive and they lack of technical skills in order to control the tool. Therefore, in directly they have some obstacle to get faster product's feedback from customers. Thus, the personal online retailing need to struggle to stay in market because they need to compete with successful online company such as G-market. Sentiment analysis also known as opinion mining. Aim of this research is develop the tool that allow user to automatic detect the sentiment comment on social media account. RAD model methodology is chosen since its have several phases could produce more activities and output. Soppy tool will be develop using Microsoft Visual. In order to generate an accurate sentiment detection, the functionality testing will be use to find the effectiveness of this Soppy tool. This proposed automated Soppy Tool would be able to provide a platform to measure the impact of the customer sentiment over the postings on their social media site. The results and findings from the impact measurement could then be use as a recommendation in the developing or reviewing to enhance the capability and the profit to their personal online retailing company.

• International Journal of Computer Science & Network Security
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• v.21 no.11
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• pp.1-10
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• 2021

Cyberbullying has become a severe issue and brought a powerful impact on the cyber world. Due to the low cost and fast spreading of news, social media has become a tool that helps spread insult, offensive, and hate messages or opinions in a community. Detecting cyberbullying from social media is an intriguing research topic because it is vital for law enforcement agencies to witness how social media broadcast hate messages. Twitter is one of the famous social media and a platform for users to tell stories, give views, express feelings, and even spread news, whether true or false. Hence, it becomes an excellent resource for sentiment analysis. This paper aims to detect cyberbully threats based on Naïve Bayes, support vector machine (SVM), and k-nearest neighbour (k-NN) classifier model. Sentiment analysis will be applied based on people's opinions on social media and distribute polarity to them as positive, neutral, or negative. The accuracy for each classifier will be evaluated.

• The Journal of Information Systems
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• v.32 no.4
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• pp.69-94
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• 2023

Purpose Social networking service (SNS) platforms employ distinct networking strategies to meet the varying needs of their users, resulting in divergent sets of technological functionalities offered by each platform. Consequently, unique features on various SNSs give rise to distinct social issues. Moreover, the available technical coping mechanisms for users vary significantly across platforms. Design/methodology/approach Therefore, this study analyzes the factors affecting technical coping intention based on technical functions of SNSs for users exposed to cybercrime, such as sexual harassment. We divide coping intention into active and passive coping intention. Furthermore, this research focuses on trust as an antecedent of coping intention and verifies how human and system-like trust affects two coping intentions in different directions. Findings Findings reveal that system-like trust significantly affects both active and passive coping intention as a belief in whether the technology will work properly. However, in the case of human-like trust, trust in the platform provider was found to negatively affect passive coping, which is considered unsocialized behavior on SNS platforms. Therefore, both human-like and system-like trust for the platform must be appropriately applied to cope with the problem while activating the platform.

• The Journal of the Korea Contents Association
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• v.19 no.1
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• pp.74-85
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• 2019

This Study explores the reason why the social media like Cyworld, Iloveschool in Korea in the viewpoint if the layered model by interview. As a result the success factor in the viewpoint of layered model, user used social media for fulfilling the need for linking with other users and the social media offers the customized contents to user. Finally the social media dominated the market in advance. Facebook and Kakao talk are good examples of successful media. The failure factors are to care less about what other users want, to limit the expand of platform and not to copy with the change of the media environment. Iloveschool, Cyworld and Twitter are the examples of failure social media in Korean society. This study highlights the importance of the sensitivity of the change of environment. The expert mentioned the importance of 4th industrial revolution technology like AI, Big data and expected that new technology will emerge and the service will be developed by the change of user's taste.

• Asia-Pacific Journal of Business
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• v.10 no.1
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• pp.73-86
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• 2019

Since its launch, WeChat has been changing the Chinese lifestyle, changing the traditional way of distribution, and changing the way companies market with the combination of information innovation and New Media. Now, WeChat plays an indispensable role in peopl's daily lives, not only in chatting software, but also in shopping, delivery, ordering, payment, and games. This study was centered on people who have used WeChat and around these backgrounds, planned study models. Through prior research, the purpose of the research is to explore the factors influencing the effects of the WeChat platform on MPR and explore the media effects of advertising attitude between WeChat platform features and MPR effects and provide basic material on its continued development. The research has shown that the reliability and diversity of the WeChat platform has a significant impact on both advertising attitude and purchase intention and propaganda intention of MPR effects. Advertising attitude has a positive impact on purchase intention and propaganda intention, and advertising attitude is shown to have a mediated effect between the WeChat platform and the MPR effects. The results of this study suggest the theoretical enlightenment of "continuous and stable development of the WeChat platform", and it is expected that marketing development plans of various social platforms will provide basic materials.

• International Journal of Advanced Culture Technology
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• v.7 no.1
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• pp.77-83
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• 2019

Recently, as social media users have grown, the resulting form of advertising has emerged, and one of the types is native advertising. This advertising method appears to be 52% higher than the banner, according to a study by the IPG Media Lab (2013). Therefore, there is a positive effect on native advertising, but it is necessary to maximize the effect. In this paper, the acceptor's attitude to the native advertisement and the shared intention are verified as to how the effect of the native advertisement can be understood and the maximized effect can be obtained. When the brand phrase was in the form of direct exposure, the subjects were positive about the advertisement and the brand attitude was favorable. Share intentions were also high. These results included suggestions to produce native advertisements in consideration of the attitudes and sharing of the recipients.