• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.11 no.11
• /
• pp.4320-4330
• /
• 2010

Blogs that allow two way communications are open to the public more than 20 million sites these days. The study tries to categorize and classify blogs based on the common representative factors. As blogs are changing dynamically, the study also tries to figure out key factors either for growing or perishing dynamics. The study develops the research idea from the independent variables such as contents factors and psychological factors to the controlling factors such as trust, attitude, and purchasing intention. The research found out that opinion leading and information seeking tendency are significantly related to the attitude to the internet shopping mall.

• The Journal of Asian Finance, Economics and Business
• /
• v.8 no.3
• /
• pp.61-67
• /
• 2021

The covid-19 pandemic scenario caused the most extensive economic shocks the world has experienced in decades. Maintaining financial performance and economic stability is essential during the pandemic period. In these conditions, where movement is severely restricted, media consumption is considered to be increasing. The social media platform is one of the media online used by the public as a source of information and also expressing their sentiment, including individual investors in the capital market as social media users. Twitter is one of the social media microblogging platforms used by individual investors to share their opinion and get information. This study aims to determine whether microblogging sentiment investors can predict the capital market during pandemics. To analyze microblogging sentiment investors, we classified sentiment using the phyton text mining algorithm and Naïve Bayesian text classification into level positive, negative, and neutral from November 2019 to November 2020. This study was on 68 listed companies on the Indonesia stock exchange. A Vector Autoregression and Impulse Response is applied to capture short and long-term impacts along with a causal relationship. We found that microblogging sentiment investor has a significant impact on stock returns and volatility and vice-versa. Also, the response due to shocks is convergent, and microblogging investors in Indonesia are categorized as a "news-watcher" investor.

• International Journal of Computer Science & Network Security
• /
• v.23 no.2
• /
• pp.13-30
• /
• 2023

Since the COVID-19 vaccine became available, people have been sharing their opinions on social media about getting vaccinated, causing discussions of the vaccine to trend on Twitter alongside certain events, making the website a rich data source. This paper explores people's perceptions regarding the COVID-19 vaccine during certain events and how these events influenced public opinion about the vaccine. The data consisted of tweets sent during seven important events that were gathered within 14 days of the first announcement of each event. These data represent people's reactions to these events without including irrelevant tweets. The study targeted tweets sent in Arabic from users located in Saudi Arabia. The data were classified as positive, negative, or neutral in tone. Four classifiers were used-support vector machine (SVM), naïve Bayes (NB), logistic regression (LOGR), and random forest (RF)-in addition to a deep learning model using BiLSTM. The results showed that the SVM achieved the highest accuracy, at 91%. Overall perceptions about the COVID-19 vaccine were 54% negative, 36% neutral, and 10% positive.

• The Journal of the Korea Contents Association
• /
• v.16 no.10
• /
• pp.766-779
• /
• 2016

This study was designed to look at a gap between what is reported and what is real, based on 'virtuality' shown in the media coverage of the Sewol ferry disaster. The way the Korean media reported the disaster raised serious concern in describing realities as the coverage was dotted with omitted, diluted, misleading, false and biased information, dubbed as the sinking of journalism by the Special Committee of the Korea Broadcasting Journalist Association. Virtuality can be problematic in journalism since users, when frequently exposed to 'mediated reality' or mediated presentment, often consider it actual and respond to it, rather than reacting to 'actual reality'. Many studies have found that media users tend to perceive mediated reality as an actual outside world. This paper aimed to explain signification of media reporting and limitations of user perception by reviewing major discussions and arguments on virtuality in previous research and history of thoughts. It was easy to link virtuality of mediated reality to the role of the media, which impact public opinion and change the flow of an event, and to other concepts such as the socialization of power, social control and social hegemony.

• Journal of Korean Port Research
• /
• v.9 no.2
• /
• pp.9-24
• /
• 1995

The intensification of the competition among container terminals has led to important affect such as, decision making or aggressive intervention of customers for terminal operation. Therefore, in case of developed ports, the large transition of port operation is composed of the press of terminal customer than decision making of terminal manager. Overall port tariffs for using terminal is made out by the conference of terminal customers than the supreme headquarters of terminal operation, and the related investment of terminal has been made according to requisition or proposal of customers. Therefore, among decision making problems that shippers, shipping companies, and freight forwarder among decision making problems that shippers, shipping companies, and freight forwarder face, the choice of the container terminal is one of the most important problems. So, the decision making of the users seems to have a significant impact on the competitive power of container terminals. The main objective of this study is to design port marketing strategy for strengthening the competitive power of container terminals. The results of this study were found as follows: Firstly, port authority should establish user-oriented operation policy of terminal as the means of activating the opinion window, using terminal monitoring system(TMS). Secondly, terminal planning and development of government should be made to minimize the lead time, to induce the civil capital and to utilize the economies of scale. Thirdly, port authority needs to endeavor to analyze the information of competing foreign terminals as well to promote the concentrated marketing for the terminal on the users, to train the expert and to develop the new port charge system. Fourthly, to improve the competitive power of the container terminal, Port Authority should optimize the subsystems related to port marketing, far more these systems should be joined organically to work effectively. Finally, port authority system should be introduced, Namely, port should have the enterprise inclination as well s the public inclination.

• International Journal of Computer Science & Network Security
• /
• v.24 no.2
• /
• pp.79-88
• /
• 2024

The use of the social media has become part of our daily life activities. The social web channels provide the content generation facility to its users who can share their views, opinions and experiences towards certain topics. The researchers are using the social media content for various research areas. Sentiment analysis, one of the most active research areas in last decade, is the process to extract reviews, opinions and sentiments of people. Sentiment analysis is applied in diverse sub-areas such as subjectivity analysis, polarity detection, and emotion detection. Stance classification has emerged as a new and interesting research area as it aims to determine whether the content writer is in favor, against or neutral towards the target topic or issue. Stance classification is significant as it has many research applications like rumor stance classifications, stance classification towards public forums, claim stance classification, neural attention stance classification, online debate stance classification, dialogic properties stance classification etc. This research study explores different feature sets such as lexical, sentiment-specific, dialog-based which have been extracted using the standard datasets in the relevant area. Supervised learning approaches of generative algorithms such as Naïve Bayes and discriminative machine learning algorithms such as Support Vector Machine, Naïve Bayes, Decision Tree and k-Nearest Neighbor have been applied and then ensemble-based algorithms like Random Forest and AdaBoost have been applied. The empirical based results have been evaluated using the standard performance measures of Accuracy, Precision, Recall, and F-measures.

• Journal of the Korean Institute of Landscape Architecture
• /
• v.37 no.6
• /
• pp.19-27
• /
• 2010

The purpose of this study is to evaluate urban parks and green spaces within the public service framework by identifying priority elements. This study surveyed 455 residents from 80 dongs(neighborhoods), of 5 Gu(districts) districts in Daejeon. The results were as follows. Regarding the evaluation of urban parks as a public service, the average survey score, of all 46 questions, was distributed from 2.46 to 3.54(Likert 5 point scale). Interesting findings can be observed in that most of the survey participants gave high scores to Daejon's natural green environments and geographical traits. That is, Daejon residents perceived their urban nature spaces as a natural geographical environment rather than a public service provided by their local government. Therefore, it seems necessary for the local government, by and large, to improve urban parks and urban green space programs. The low scoring items were 'citizen's participation'(mean 2.46), 'acceptance of complaints, comments, and improvement proposals'(mean 2.54), 'citizen's respect', 'inclusive design' (for the physically challenged-mean 2.55), 'diverse programs and activities in the urban park'(mean 2.55) and 'implementation of revision proposals by citizens'(mean 2.61). These results indicate that citizen participation in planning and opinion sharing is needed to build public services that are satisfactory to users. To evaluate the park and green space from the viewpoint of public services is a useful method with a new point of view. In accordance with this study, the factor of 'supply decision maker' is a statistically meaningful variable of resident satisfaction while earlier studies on the satisfaction studies of physical environment, hardly discovered variables on 'supply decision maker', 'acceptance of resident opinions', and 'information usage'. Responding to or taking positive action according to significant factors, such as the findings of this study, can expand the role of public officials to exert a more positive influence on urban parks and green spaces.

• The Journal of the Korea Contents Association
• /
• v.16 no.9
• /
• pp.751-768
• /
• 2016

The success of the journey to the west of tvN's shows the positive prospect of web entertainment. This study highlights how viewers actively select web progrmas and how they diffuse the infomrmation of web programs to explore the possibility of success of web program and the change of viewing environment. This study revealed the attention of viewers affected the diffusion of programs via social media. The highness of the viewer's attention cause the highness of active interaction between users. The production company of web entertaninment has to focus on the high hits strategy. In the view of journalists, they covered on the appearance of the heroin rather than the content of the program. The relationship of viewing type and viral type via SNS is related with the activity of viewers. If viewers participate in viewing they express their opinion on the web entertainment actively.

• Journal of Intelligence and Information Systems
• /
• v.19 no.3
• /
• pp.141-156
• /
• 2013

Social media is a representative form of the Web 2.0 that shapes the change of a user's information behavior by allowing users to produce their own contents without any expert skills. In particular, as a new communication medium, it has a profound impact on the social change by enabling users to communicate with the masses and acquaintances their opinions and thoughts. Social media data plays a significant role in an emerging Big Data arena. A variety of research areas such as social network analysis, opinion mining, and so on, therefore, have paid attention to discover meaningful information from vast amounts of data buried in social media. Social media has recently become main foci to the field of Information Retrieval and Text Mining because not only it produces massive unstructured textual data in real-time but also it serves as an influential channel for opinion leading. But most of the previous studies have adopted broad-brush and limited approaches. These approaches have made it difficult to find and analyze new information. To overcome these limitations, we developed a real-time Twitter trend mining system to capture the trend in real-time processing big stream datasets of Twitter. The system offers the functions of term co-occurrence retrieval, visualization of Twitter users by query, similarity calculation between two users, topic modeling to keep track of changes of topical trend, and mention-based user network analysis. In addition, we conducted a case study on the 2012 Korean presidential election. We collected 1,737,969 tweets which contain candidates' name and election on Twitter in Korea (http://www.twitter.com/) for one month in 2012 (October 1 to October 31). The case study shows that the system provides useful information and detects the trend of society effectively. The system also retrieves the list of terms co-occurred by given query terms. We compare the results of term co-occurrence retrieval by giving influential candidates' name, 'Geun Hae Park', 'Jae In Moon', and 'Chul Su Ahn' as query terms. General terms which are related to presidential election such as 'Presidential Election', 'Proclamation in Support', Public opinion poll' appear frequently. Also the results show specific terms that differentiate each candidate's feature such as 'Park Jung Hee' and 'Yuk Young Su' from the query 'Guen Hae Park', 'a single candidacy agreement' and 'Time of voting extension' from the query 'Jae In Moon' and 'a single candidacy agreement' and 'down contract' from the query 'Chul Su Ahn'. Our system not only extracts 10 topics along with related terms but also shows topics' dynamic changes over time by employing the multinomial Latent Dirichlet Allocation technique. Each topic can show one of two types of patterns-Rising tendency and Falling tendencydepending on the change of the probability distribution. To determine the relationship between topic trends in Twitter and social issues in the real world, we compare topic trends with related news articles. We are able to identify that Twitter can track the issue faster than the other media, newspapers. The user network in Twitter is different from those of other social media because of distinctive characteristics of making relationships in Twitter. Twitter users can make their relationships by exchanging mentions. We visualize and analyze mention based networks of 136,754 users. We put three candidates' name as query terms-Geun Hae Park', 'Jae In Moon', and 'Chul Su Ahn'. The results show that Twitter users mention all candidates' name regardless of their political tendencies. This case study discloses that Twitter could be an effective tool to detect and predict dynamic changes of social issues, and mention-based user networks could show different aspects of user behavior as a unique network that is uniquely found in Twitter.

• The Journal of KAIRB
• /
• v.4 no.1
• /
• pp.16-22
• /
• 2022

Purpose: The traditional ethical study only suggests a blurred insight on the research using medical big data, especially in this rapid-changing and demanding environment which is called "4th Industry Revolution." Current institutional/ethical issues in big data research need to approach with the thoughtful insight of past ethical study reflecting the understanding of present conditions of this study. This study aims to examine the ethical issues that are emerging in recent health care big data research. So, this study aims to survey the public perceptions on of health care big data as part of the process of public discourse and the acceptance of the utility and provision of big data research as a subject of health care information. In addition, the emerging ethical challenges and how to comply with ethical principles in accordance with principles of the Belmont report will be discussed. Methods: Survey was conducted from June 3th August to 6th September 2020. The online survey was conducted through voluntary participation through Internet users. A total of 319 people who completed the survey (±5.49%P [95% confidence level] were analyzed. Results: In the area of the public's perspective, the survey showed that the medical information is useful for new medical development, but it is also necessary to obtain consents from subjects in order to use that medical information for various research purposes. In addition, many people were more concerned about the possibility of re-identifying personal information in medical big data. Therefore, they mentioned the necessity of transparency and privacy protection in the use of medical information. Conclusion: Big data on medical care is a core resource for the development of medicine directly related to human life, and it is necessary to open up medical data in order to realize the public good. But the ethical principles should not be overlooked. The right to self-determination must be guaranteed by means of clear, diverse consent or withdrawal of subjects, and processed in a lawful, fair and transparent manner in the processing of personal information. In addition, scientific and ethical validity of medical big data research is indispensable. Such ethical healthcare data is the only key that will lead to innovation in the future.