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- P-ISSN1738-6764
- E-ISSN2093-7504
- KCI
ISSN : 1738-6764
Vol.13 No.1
Abstract
The study aims to reveal the differences in the factors influencing portal news and news site application usages on smartphones in regard to political discussion networks, news use across multiple media platforms and news genre consumption. The results demonstrate that those factors affected both types of application usages in a different manner when controlling for demographics. The more participants conversed politics with homogeneous networks, the more they used portal news on smartphones. Conversely, the more political discussion with heterogeneous networks, the more they used news site application on smartphones. The more frequently Internet and mobile phone were employed for news source and the more soft news genre was consumed, the more the portal news application was used. However, the more frequently traditional and social media were employed for news source and the more hard news consumed, the more news site application was used. The findings imply that portal news application users may increase their likelihood of soft news consumption using Internet and mobile phones for political discussion with close social relations, while news site application users may increase their likelihood of hard news consumption using traditional and social media for political discussion with distant social relations.
Abstract
This study focused on realizing the UX pattern elements for Wordpress service, and applying the UX pattern approach to enhance UX consideration in Wordpress theme service. The Wordpress UX pattern system was developed based on web UX pattern analysis, and on characteristics of Wordpress components and theme filtering tags. The Wordpress UX pattern system was further analyzed in 22 popular Wordpress themes and 20 web UX scenarios, to evaluate its working by defining theme UX as a case study. The Wordpress theme filtering service GUI was designed based on the Wordpress UX pattern system as a design suggestion. Web technology is evolving rapidly, and web design has become a ready-made service with less user experience consideration, or design creativity. This study directs to keep track of UX value in an emerging web service paradigm.
Abstract
The diffusion of advanced mobile technology has introduced new types of personal information or ‘location data’. These new data mean new opportunities for businesses, such as location-based services (LBS), but have resulted in new consumer anxieties regarding disclosure of personal information. This study examines the effects of the consumers’ perceived control over “time-and-place” information in location-aware services on their perceived privacy risk. A total of 270 respondents participated in this study. Conditions of perceived privacy control were operationalized over time-and-place information, in a 2x2 factorial design. Results indicate that the perceived control over time-and-place personal information is a significant predictor of perceived risk, and control assurances over time-and-place information enhances the perception of control, thus alleviating the perceived risk. In addition, the effect is much more significant when time and place were combined.
Abstract
Using the network analysis method, this study investigates the communication structure of Open Data on the Twitter sphere. It addresses the communication path by mapping influential activities and comparing the contents of tweets about Open Data. In the years 2015 and 2016, the NodeXL software was applied to collect tweets from the Twitter network, containing the term “opendata”. The structural patterns of social media communication were analyzed through several network characteristics. The results indicate that the most common activities on the Twitter network are related to the subjects such as new applications and new technologies in Open Data. The study is the first to focus on the structural and informational pattern of Open Data based on social network analysis and content analysis. It will help researchers, activists, and policy-makers to come up with a major realization of the pattern of Open Data through Twitter
Abstract
Increased use of software and complexity of software functions, as well as shortened software quality evaluation periods, have increased the importance and necessity for automation of software testing. Automating software testing by using machine learning not only minimizes errors in manual testing, but also allows a speedier evaluation. Research on machine learning in automated software testing has so far focused on solving special problems with algorithms, leading to difficulties for the software developers and testers, in applying machine learning to software testing automation. This paper, proposes a new machine learning framework for software testing automation through related studies. To maximize the performance of software testing, we analyzed and categorized the machine learning algorithms applicable to each software test phase, including the diverse data that can be used in the algorithms. We believe that our framework allows software developers or testers to choose a machine learning algorithm suitable for their purpose.
Abstract
Carbon Capture and Storage (CCS) technologies involve three major stages, i.e., capture, transport, and storage. The transportation stage of CCS technologies has received relatively little attention because the requirements for CO2 transport differ based on the industry-related conditions, geological, and demographical characteristics of each country. In this study, we analyzed the properties of CO2 transport using a pipeline. This study has important implications for ensuring the stability of a long-term CCS as well as the large cost savings, as compared to the small cost ratio as a percentage of the entire CCS system. The state of CO2, network topologies, and node distribution are among the major factors that influence CO2 transport via pipelines. For the analysis of the properties of CO2 transport using a pipeline, the CO2 pipeline connections were visualized by the simulator developed by Lee [11] based on the network topologies in CO2 transport. The case of Korean CCS technologies was applied to the simulation.
Abstract
Recently, the Social Internet of Things (IoT), the follow-up of the IoT, has been studied to expand the existing IoT services, by integrating devices into the social network of people. In the Social IoT environment, humans, devices and digital contents are connected with social relationships, to guarantee the network navigability and establish levels of trustworthiness. However, this environment handles massive data, including social data of humans (e.g., profile, interest and relationship), profiles of IoT devices, and digital contents. Hence, users and service providers in the Social IoT are exposed to arbitrary data when searching for specific information. A study about the recommender system for the Social IoT environment is therefore needed, to provide the required information only. In this paper, we propose the Social correlation group based Recommender System (SRS). The SRS generates a target group, depending on the social correlation of the service requirement. To generate the target group, we have designed an architecture, and proposed a procedure of the SRS based on features of social interest similarity and principles of the Collaborative Filtering and the Content-based Recommender System. With simulation results of the target scenario, we present the possibility of the SRS to be adapted to various Social IoT services.
Abstract
This study attempts to explain how communication technology impacts global creative trends. We explore global creative trends based on award-winning creative topics presented at the 2016 Cannes Lions International Festival of Creativity . After analyzing award-winning topics, five main creative trends were selected with the keywords: technology, story-telling, social media, causes, and humor. The 2016 Cannes Lions Festival demonstrated that technology (i.e., virtual reality, artificial intelligence) has expanded the limits of creativity. Story-telling is still considered to be effective for raising audience attention. Social media enhances consumer engagement while nurturing future consumer relationships. Supporting social causes allows companies to garner goodwill from the public. Humor is powerful when it appropriately appeals to both products and customers.
Abstract
Interactive Typography is a process where a user communicates by interacting with text and a moving factor. This research covers interactive typography using real-time response to a user’s gesture. In order to form a language-independent system, preprocessing of entered text data presents image data. This preprocessing is followed by recognizing the image data and the setting interaction points. This is done using computer vision technology such as the Harris corner detector and contour detection. User interaction is achieved using skeleton information tracked by a depth camera. By synchronizing the user’s skeleton information acquired by Kinect (a depth camera,) and the typography components (interaction points), all user gestures are linked with the typography in real time. An experiment was conducted, in both English and Korean, where users showed an 81% satisfaction level using an interactive typography system where text components showed discrete movements in accordance with the users’ gestures. Through this experiment, it was possible to ascertain that sensibility varied depending on the size and the speed of the text and interactive alteration. The results show that interactive typography can potentially be an accurate communication tool, and not merely a uniform text transmission system.
Abstract
This paper compares the difference in the degree of advertising avoidance between traditional media and the Internet. The study also examines customers’ beliefs, attitudes, and behavior toward advertising to build a theoretical model that explains advertising avoidance. A survey was conducted to identify the influential factors. Findings indicate that on comparison, YouTube advertisements on the Internet were more problematic than TV commercial breaks, leading to high advertising avoidance on the part of consumers. Finally, using path analysis, a general advertising avoidance model based on the belief-attitude-behavior hierarchy is tested. The model shows that certain beliefs about advertising have direct effects on advertising avoidance behavior as well as on the attitude toward advertising.