A social networking service (SNS) is a system that allows users to freely communicate with each other to form a network of social connections and expand their network of contacts. Companies and brands use SNS marketing to provide information by creating their own content and sending it to consumers. Since companies can freely express the information they want to convey, it has become important to establish a promotional strategy that can increase consumers' intention to buy. Therefore, in this study, we categorized SNS posts into simple product exposure and ostentatious self-expression, and selected the product type to find out how consumers form attitudes toward SNS posts. The experimental design was a 2X2 factorial design with SNS post type (simple exposure, ostentatious self-expression) x product type (material goods, experiential goods), and 92 college students were tested. The results of the study showed that there was an interaction effect between SNS post type and product type, which supported the research hypotheses H1 to H3. In addition, this study attempted to verify the structural relationship between consumer attitude toward SNS posts and purchase intention through product attitude. It was found that product attitude fully mediated between consumer attitude and purchase intention. Therefore, this study empirically examined consumer attitudes toward various types of posts to determine which types of posts trigger SNS users' purchase intentions. We also confirmed the mediating effect of consumer attitude on product attitude and intention to purchase. Therefore, based on the differences in SNS users' attitudes when posting their products, this study suggests an efficient SNS marketing strategy for companies to shape product attitudes and purchase intentions.

Recently, public interest in blockchain is increasing as the Financial Services Commission overhauled the token securities issuance (STO) discipline system in 2023 and the Bank of Korea plans to test the actual transaction of the central bank's digital currency (CBDC) in 2024. These regulatory changes suggest the possibility that financial transactions based on blockchain will be incorporated into the institutional sphere. When blockchain-based financial transactions such as CBDC are introduced in Korea, the basis for regulations to ensure safety will be the Electronic Financial Transactions Act and the Electronic Financial Supervisory Regulations. In addition, blockchains applied to current financial transactions must also comply with the Electronic Financial Transactions Act and the Electronic Financial Supervisory Regulations. However, since information recorded on the blockchain is difficult to modify or delete, and it is distributed and stored, there is a limit to applying the existing regulations based on the centralized system as it is. Therefore, regulations such as control of the computer ledger and destruction of electronic financial transaction information, provision and confidentiality of electronic financial transaction information, interpretation of information processing, backup and production in the event of an accident, and establishment of a disaster recovery center emerge as issues of securing safety. Financial authorities need to come up with a supervisory plan for blockchain-based financial services to respond to the new concept of a distributed ledger, and the regulation should be enacted and revised by strengthening the parts to be strengthened in the current regulation and deleting the parts to be deleted. In this study, specific policy countermeasures such as expanding the control of the computer ledger and anonymous processing means, reorganizing the scope of information provision and establishing a standard model, interpreting it as an electronic financial assistant and program, distinguishing clear roles and strengthening solidarity responsibility, and reflecting high operational resilience characteristics were proposed.

This study aims to provide suggestions for a paradigm shift in the Korean government platform in the era of virtual society. We have examined examples of digital governance construction implemented in major advanced countries and derived 13 tasks in four areas for the construction of digital platform governance in Korea. In other words, the Korean government must 1) be a government that runs national affairs based on AI and data, 2) a government that does a good job through digital transformation, 3) a government that provides preemptive customized services, and 4) a government that aims for a convenient and safe digital inclusive society. We have proposed 13 specific detailed tasks and key promotion plans for paradigm shift, which we hope will help the Korean government to quickly establish a digital platform governance for public-private cooperation.

Recently, as social anxiety regarding violent crimes accompanied by frequent occurrences of violence has increased, the need for intelligent video analysis in CCTV systems for crime prevention and rapid response to incidents has grown. One of the methods used for detecting violent behavior through video analysis is action-based detection using pose estimation. However, relying solely on joint angles and changes obtained from pose estimation to detect violent acts can lead to issues. False positives occur when non-violent actions such as petting a head or hugging are mistakenly classified as violent behavior. This study aims to reduce the frequency of false positives in action-based violence detection methods that utilize only pose estimation. We propose a new violence detection method that combines the results of facial emotion recognition (anger, disgust, fear, sadness, surprise, happiness, and neutrality) of the expected victim with the existing pose estimation-based violence detection method. By combining pose estimation with facial emotion recognition results on a video dataset consisting of YouTube videos and self-made videos, we were able to achieve a higher accuracy rate of 92.5% compared to the traditional method which solely relies on pose estimation. Future research will focus on studying violence detection in actual CCTV scenarios to improve the reliability of the result data.

In order to promote the AI applications in the financial industry, the financial sector has recently been paying attention to synthetic data technology. Synthetic data generates using a purpose-built mathematical model or algorithm, with the aim of solving a set of data science tasks. This study evaluates the utility of synthetic data by analyzing heterogeneous tabular data that is composed of discrete, categorical and continuous variables and has the feature of unbalanced data, which is commonly found in the financial sector. As a synthetic data generation technique, the TGAN and CTGAN models are applied by considering the feature of tabular data. As a result of evaluating the utility in terms of resemblance and machine learning efficiency, those of TGAN are confirmed to be high, while the quality of CTGAN are relatively poor. This is interpreted to be particularly due to the generation of categorical variables, and it suggests that how those with categorical properties especially are considered in the synthetic data generation model is a major factor in determining the utility of generation synthetic data.

This paper explores the viability of investment opportunities through earning rewards as validators in blockchain networks, moving beyond traditional approaches to cryptocurrency investment. Recently, there has been growing interest in participating as blockchain validators to receive stable rewards, rather than merely purchasing and holding cryptocurrencies. This shift reflects a perception among investors that participating in blockchain validation is a safer investment method. Despite this, most investment decisions still focus primarily on the volatility of cryptocurrency prices, with investment strategies considering validator reward rates being relatively underexplored. This study selects five major cryptocurrencies based on the Proof of Stake (PoS) mechanism (Ethereum, Cosmos, BNB, Polkadot, Polygon) and compares the validator reward rates from the fourth quarter of 2022 to the fourth quarter of 2023. The selected cryptocurrencies were chosen based on their market capitalization, validator reward rates, and the number of wallets staked, representing popular and trustworthy options. Through this analysis, the research applies Modern Portfolio Theory (MPT) by Harry Markowitz to propose a method of portfolio composition that maintains an optimal balance between risk and return. This is expected to contribute to investors making more stable and sustainable investment decisions based on the fundamental value and long-term growth potential of blockchain technology. Additionally, this study is anticipated to provide significant insights into academic discussions related to cryptocurrency investments, deepen understanding of the cryptocurrency market, and enhance the efficiency of investment strategies.

This study aims to analyze the importance of revitalizing residential tourism. As the global tourism trend shifts from stopover visits to stay-at-home tourism, interest in stay-at-home tourism is increasing, and the government is also providing a lot of budget support. In particular, a lot of research is being conducted in the academic field on policy areas for residential tourism. However, most studies stop at suggesting policies. In this study, the importance of revitalizing residential tourism was derived focusing on city and tourism experts. First, three Delphi surveys were conducted with 12 experts, and four major factors (residence-type tourism marketing strategy, residence-type tourism infrastructure, residence-type tourism products, attraction of residence-type tourists) and 16 lower-level factors were derived. A structured questionnaire was created focusing on this indicator, and AHP (Analytic Hierarchy Process) analysis was conducted on 30 experts. As a result of the AHP analysis, the factor with the highest importance among the top factors was lodging-type tourism products, followed by attraction of lodging-type tourists and lodging-type tourism infrastructure. Among the 16 sub-factors, the most important factor was analyzed as incentives for participating companies. The results of this study provided empirical implications for the policies being promoted by the government, local governments, and private operators to revitalize residential tourism cities.