• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.1-17
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• 2014

The proliferation of using social media and social networking services affects the lifestyles of people. These phenomena are useful to companies that wish to promote and advertise new products or services through these social media; these social media venues also come with large amounts of user data. However, studies that analyze the data of social media within the perspective of information exchanges are hard to find. Much of the previous research in this area is focused on measuring the performance of exhibitions using general statistical approaches and piecemeal measures. Therefore, in this study, we want to analyze the characteristics of information exchanges in social media by using Twitter data sets, which are relating to the Mobile World Congress (MWC). Using this methodology provides exhibition organizers and exhibitors to objectively estimate the effect of social media, and establish strategies with social media use. Through a user network analysis, we additionally found that social attributes are as important as the popular attribute regarding the sustainability of information exchanges. Consequently, this research provides a network analysis using the data derived from the use of social media to communicate information regarding the MWC exhibition, and reveals the significance of social attributes such as the degree and the betweenness centrality regarding the sustainability of information exchanges.

• Journal of Internet Computing and Services
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• v.24 no.4
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• pp.127-135
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• 2023

This research paper explores the application of FinBERT, a variational BERT-based model pre-trained on financial domain, for sentiment analysis in the financial domain while focusing on the process of identifying suitable training data and hyperparameters. Our goal is to offer a comprehensive guide on effectively utilizing the FinBERT model for accurate sentiment analysis by employing various datasets and fine-tuning hyperparameters. We outline the architecture and workflow of the proposed approach for fine-tuning the FinBERT model in this study, emphasizing the performance of various datasets and hyperparameters for sentiment analysis tasks. Additionally, we verify the reliability of GPT-3 as a suitable annotator by using it for sentiment labeling tasks. Our results show that the fine-tuned FinBERT model excels across a range of datasets and that the optimal combination is a learning rate of 5e-5 and a batch size of 64, which perform consistently well across all datasets. Furthermore, based on the significant performance improvement of the FinBERT model with our Twitter data in general domain compared to our news data in general domain, we also express uncertainty about the model being further pre-trained only on financial news data. We simplify the complex process of determining the optimal approach to the FinBERT model and provide guidelines for selecting additional training datasets and hyperparameters within the fine-tuning process of financial sentiment analysis models.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.6
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• pp.2707-2712
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• 2012

Desktop-based computing environment is changed into mobile computing using smart phone and cloud computing providing common behavior and big data by network. Because of this transformation software development and operating environment is changed into heterogeneous distributed environment. As a result, dynamic service composition or changement is required. However, there is few research of techniques supporting service composition or changement dynamically in this situation. This paper suggests a technique for customizing services dynamically of mobile applications based on android platform. Especially we propose a customization technique of service by applying ontology technique to improve sharing and reuse of service. We applied proposed technique into meeting notification system, and obtain that it can be customized into various services such as email, sms, twitter service, and so on.

• The Journal of the Korea Contents Association
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• v.15 no.4
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• pp.407-419
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• 2015

As the use of social media has gained mainstream popularity, concerns on the particulars of the users' motivation and method of use is on the rise. Under uses and gratifications approach, this study analyzes the use behaviors in Kakao-story, Facebook, and Twitter, and analyzes the changes in the perception of social support by the users of the media. Data was analyzed from 240 online questionnaire surveys. The study finds that the frequency of use of social media differs depending upon the personality of the users and their purpose of use, both of which also influence their type of use. It also finds that frequent use of social media increased the users' perception of social support, whereas their type of use had no effect with such perception. Communication behavior through social media seem to increase perception of social support.

• The Journal of Bigdata
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• v.2 no.1
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• pp.27-39
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• 2017

The importance of online communication is getting increased by the rapid growth of smartphone supply and Social Network Service (SNS) use. Catching up with the trend, firms are actively use SNS to improve brand image, promote products, and communicate with customer. On the one hand, SNS is the channel for firms' marketing activities, but on the other, it is also the channel where the events related to the firms propagate in real time. Firms are led to unexpected state of crisis, when events are quickly spread out on SNS. Then firms are assessed their image by the way they deal with the state of crisis. This paper proposes to figure out user response on SNS according to each crisis response strategies by analyzing event-related twitter data when crisis situations of firms arise. We classify crisis response strategies into response attitude, defensive and accommodative response, and response speed, fast and slow response. This paper suggests optimal crisis response strategy to firms regarding state of crisis propagated on SNS.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.3
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• pp.292-297
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• 2014

As a Social Network Service (SNS) has become an integral part of our everyday lives, millions of users can express their opinion and share information regardless of time and place. Hence sentiment analysis using micro-blogs has been studied in various field to know people's opinion on particular topics. Most of previous researches on movie reviews consider only positive and negative sentiment and use it to predict movie rating. As people feel not only positive and negative but also various emotion, the sentiment that people feel while watching a movie need to be classified in more detail to extract more information than personal preference. We measure sentiment distributions of each movie from tweets according to the Thayer's model. Then, we find similar movies by calculating similarity between each sentiment distributions. Through the experiments, we verify that our method using micro-blogs performs better than using only genre information of movies.

• The Research Journal of the Costume Culture
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• v.22 no.5
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• pp.848-861
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• 2014

This research was designed to conduct research to apprehend fashion brand's mobile SNS characteristics in depth and the related consumer psychology and behaviors such as brand attachment and brand loyalty. The fashion brand's mobile SNS characteristics were differentiated from the web-based fashion brand's SNS. This study targeted women in their 20s using mobile Facebook and mobile Twitter, and residing in Seoul or Gyeonggi province. Total 412 observations were collected through online survey. The major findings of the study were as follows. First, as the characteristics of fashion brand's mobile SNS, ease of fashion data storage, fashion recentness, fashion usefulness, and fashion accessibility were extracted. As the factors of the flow, time distortion/focused attention and playfulness were extracted. Second, the fashion recentness and fashion usefulness showed positive influence to time distortion/focused attention factor in the flow. All four fashion brand's mobile SNS characteristics showed positive influence to playfulness factor in the flow. Third, time distortion/focused attention factor and playfulness factor both showed positive influence to brand attachment and brand loyalty from using fashion brand's mobile SNS. Fourth, brand attachment had positive influence to brand loyalty from using fashion brand's mobile SNS. Based on the above results, this study provided practical ways to develop effective mobile SNS marketing strategies in fashion brand. Also, this study demonstrated feasible future contents and necessary improvement for fashion brand's mobile SNS, which holds marketing implications.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.24 no.3
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• pp.157-180
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• 2013

With increasing interest in content marketing, SNS (social networking services) has become more popular as a method of library marketing, both at home and abroad. Accordingly, this study analyzed the operational status and problems of library SNS marketing, in an attempt to find ways to optimize its use. Results show that librarians' opinions of library marketing and library SNS marketing were very high, but the problems they faced included a lack of human resources dedicated to marketing, lack of marketing education, a lack of content to upload each week, and low numbers of contacts on social networking sites. To further develop and optimize library SNS marketing, five solutions were suggested based on the survey results: first, composing an intensive managing team for effective SNS operation; second, providing different levels of marketing training to decrease the librarians' mistakes; third, updating data continuously; fourth, providing information and services users need; and lastly, clearly identifying each channel's active operation goals.

• The Journal of the Korea Contents Association
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• v.21 no.5
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• pp.105-117
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• 2021

This study examined the factors that influence the emotional expression in comments on the hot news about the 'Restaurant Collapse in Linfen City, Shanxi Province' published in Sina Weibo.. As a result of the study, first, there were differences in emotional expression according to gender. Women expressed stronger anger, disappointment, sadness, and condemnation than men. Second, the intensity of emotional expression of users in the eastern region was significantly higher than that of users in the central and western region. Third, the greater the number of Weibo, the total number of blogs where users participated in comments and posted emotional expressions, the stronger the emotional expression was. Fourth, unauthenticated users showed stronger emotional expressions of disappointment and sadness than authenticated users. The results of this study present implications for the factors influencing emotional expression on hot news. This study is meaningful in that it can be compared with social networks such as Twitter and Facebook in the West by looking at the factors that influence emotional expression in the process of online public opinion formation in China, and also meaningful in that a big data analysis method was used in online news analysis.

• Journal of dental hygiene science
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• v.21 no.4
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• pp.260-266
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• 2021

Background: The purpose of the study was to evaluate the relationship and route of dental Social Media marketing by age group and support effective dental marketingy by age group. Methods: A study was conducted on 265 people, aged 20 to 64 years, who lived in Seoul, Gyeonggi area and regularly used one or more of the social media platforms, Naver Band, Facebook, Instagram, KakaoStory, Twitter, or YouTube more than once a day. A 27-question questionnaire survey of approximately 10 minutes was conducted, and the collected data was statistically analyzed using the PASW program, with the significane level set to 0.05. Results: "Introduction of acquaintances" was the most common route to visit the dentist. Regarding the use of social media platforms based on age group, 'Instagram' had the highest frequency among people belonging to the age groups of 20 to 29 years and 30 to 39 years; 'YouTube' had the highest frequency among those aged 40 to 49 years; and 'Naver Band' had the highest frequency among those aged 50 to 65 years. Conclusion: The most frequently used social media by consumers according to age included Facebook, YouTube, and Instagram. However, social media was found to have no significant impact on the choice of dental institutions, as the number of people who visited the dentist through "Introduction of acquaintances" was the highest, and "Introduction of acquaintances" did not have experience accessing the dentist site after dental marketing. If this study could provide customized marketing information for each age group through social media, it is expected that the marketing effect of dental institutions through social media would be maximized in the future.