• Korean journal of communication and information
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• v.60
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• pp.172-192
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• 2012

Over the last ten years, media convergence and multiple platform expansion have affected the ways that people watch conventional television. In the post-TV era, the growing use of the Internet and mobile multi-media devices, such as smart phones, as well as the availability of abundant television content, allows television consumption to be more personalized, diversified, and linked with various media activities, especially social media uses. This study attempts to examine how television viewing experiences have been transformed with the development of the trans-media uses. Based on Walter J. Ong's concept of relation-ism, which posits that new media transform the meanings and relevance of old media rather than making old media obsolete, this study will pay particular attention to how the cultural meanings of television viewing have been redefined in the post-TV era. For the examination, this study has looked at concrete cases of the television viewing experiences of 29 young people in their twenties. Based on in-depth interview data, this study discusses the newly emerging characteristics of television viewing, its temporal and spatial experiences, and the significance of television as a medium and as a social place.

• Korean journal of communication and information
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• v.49
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• pp.20-38
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• 2010

This paper was attempting to identify determinants of media repertoires based on new services and technologies. Using the regression and discriminant models, this study examined determinants that included five independent factors such as the degree of innovation, social networks, social influences, demographic variables and media uses. The analyses revealed that all of independent variables except the degree of innovation were significant determinants of media repertoires. Secondly, the results of discriminant analyses showed that terrestrial television use, age, disposable income were significant factors discriminating new media service adopters from the sample. For new media related technologies adopters, family income, and media uses such as newspaper, Internet and radio were significant discriminant variables.

• 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.

• Journal of Public Diplomacy
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• v.2 no.1
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• pp.43-68
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• 2022

Multiple modes of communication on social media can contribute to public diplomacy in informing, conversing, and networking with members of foreign publics. However, manipulative behaviours on social media, prevalent especially in high tension contexts, create disruptions to authentic communication in what could be grey/black propaganda or information warfare. This study reviews existing literature about models of public diplomacy to guide an empirical study of China's communication in the #SouthChinaSea conversation on Twitter. It uses computational methods to identify, record, and analyze one-way, two-way, and network communication of China's actors. It employs manual qualitative research to determine the nature of China's actors. On that basis, it assesses China's Twitter communication in the issue against various models of public diplomacy.

• Journal of Internet Computing and Services
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• v.18 no.2
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• pp.97-104
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• 2017

This study explored the potential associations among older adults' online community uses, socialization, and social isolation. Results from the hierarchical regression analysis indicated that the quality and size of personal networks composed of online community members positively influences older adults' socialization and reduces social isolation. However, the frequency of meeting with online community members in offline settings was not significantly associated with socialization. Moreover, the amount of time using online communities indirectly and significantly affected social isolation, mediated by socialization. Results from this study address the positive roles of online community uses in overcoming psychological difficulties among elderly people.

• Informatization Policy
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• v.26 no.3
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• pp.36-52
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• 2019

The use of social media in government has expanded steadily around the world on the basis of Web 2.0 technology. The government uses social media as a tool for enhancing transparency, participation, collaboration, and saving costs. However, the use of social media in the public sector has not only been positive. It has also been described as a double-edged sword. Most local governments in South Korea use social media for a variety of reasons but there has not been enough practical study of the effectiveness of social media use in the public sector. Local governments generally have positive views of their social media use but the real application of social media is not consistent in each local government. This study tried to determine the reality of social media use in local government and what factors influenced its use. The research analyzed the data from a survey conducted by the Korea Local Information Research & Development Institute (KLID) in 2015 and data from Facebook in each local government. The results show that most local governments were using Facebook for promotional purposes and local government officials similarly recognized that they were using Facebook well. However, local governments showed great differences in their use and practical effect. Meanwhile, the study found that population, financial independence, level of government, the entity operating social media, the median age, and whether social media are used for interaction or to gather opinions were the most influential factors that make a difference in utilization in local government.

• Journal of Technology Innovation
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• v.29 no.4
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• pp.125-160
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• 2021

Unlike existing social platforms that seek openness, an audio-based social platform is characterized by its limitations. This study uses the Value-Based Acceptance Model(VAM) to analyze the role that such limitations play in the user's acceptance of audio-based social media. In this study, restrictive properties are defined as access-limitation, communication-limitation, and content-limitation. This study aims to analyze the effect of each variable on the perceived value and usage of audio-based social media. The hypothesis test was conducted based on the survey responses total of 207 users and potential users. The results was analyzed that three limiting variables affect perceived benefit factors, usefulness and playfulness, and the user's acceptance intention. This study is significant in that it presents a model based on the VAM and provides guidance for new forms of social media growth.

• Journal of Korean Institute of Industrial Engineers
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• v.42 no.1
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• pp.50-56
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• 2016

Social media (SM) for expressing thoughts and opinions of people in network communities can support collaboration among stakeholders in business activities. To enhance collaboration for product design, this study integrates SM with a product data management (PDM) system that manages main product development processes and data in manufacturing companies. This study proposes a text messaging SM model that shares core components of PDM systems and uses product structures in PDM systems as networks for SM broadcasting. The SM model is implemented with a research purpose PDM system and applied to product design experiments to show feasibility of the proposed SM model in PDM systems.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.5
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• pp.445-454
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• 2021

Leader and leadership are one of the important aspects in the life of a country. This study aims to predict the intention of young voters to vote for state leader elections by expanding the theory of planned behavior to the Indonesian context. Apart from the importance of the presidential election, research rarely uses the theory of planned behavior, and to the best of researchers' knowledge, there are no studies that have applied the theory of planned behavior to predict the intention to vote for the president. Therefore, this study is an attempt to fill that gap. Two hundred questionnaires were distributed using non-probability purposive sampling. Data analysis was carried out using the structural equation modeling (SEM) approach. The results showed that attitude and behavior control were positively related to voters' intention to elect presidential candidates. Furthermore, information from social media also has a positive relationship with the attitude of choosing presidential candidates. However, the results also show that subjective norms do not have a significant relationship with voters' intention. This study contributes knowledge to researchers, practitioners, and policymakers about the factors that influence youth intention to vote in Indonesia, namely, attitudes, perceived behavior control, and information from social media.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.1
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• pp.51-73
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• 2023

Social media play a significant role in communicating information across the globe, connecting with loved ones, getting the news, communicating ideas, etc. However, a group of people uses social media to spread fake information, which has a bad impact on society. Therefore, minimizing fake news and its detection are the two primary challenges that need to be addressed. This paper presents a multi-modal deep learning technique to address the above challenges. The proposed modal can use and process visual and textual features. Therefore, it has the ability to detect fake information from visual and textual data. We used EfficientNetB0 and a sentence transformer, respectively, for detecting counterfeit images and for textural learning. Feature embedding is performed at individual channels, whilst fusion is done at the last classification layer. The late fusion is applied intentionally to mitigate the noisy data that are generated by multi-modalities. Extensive experiments are conducted, and performance is evaluated against state-of-the-art methods. Three real-world benchmark datasets, such as MediaEval (Twitter), Weibo, and Fakeddit, are used for experimentation. Result reveals that the proposed modal outperformed the state-of-the-art methods and achieved an accuracy of 86.48%, 82.50%, and 88.80%, respectively, for MediaEval (Twitter), Weibo, and Fakeddit datasets.