Analysis of the present and future of the Korea online platform regulation using latent dirichlet allocation

Mun, Junhwan Article Analysis of the present and future of the Korea online platform regulation using latent dirichlet allocation Global Business & Finance Review (GBFR) Provided in Cooperation with: People & Global Business Association (P&GBA), Seoul Suggested Citation: Mun, Junhwan (2024) : Analysis of the present and future of the Korea online platform regulation using latent dirichlet allocation, Global Business & Finance Review (GBFR), ISSN 2384-1648, People & Global Business Association (P&GBA), Seoul, Vol. 29, Iss. 3, pp. 16-29, https://doi.org/10.17549/gbfr.2024.29.3.16 This Version is available at: https://hdl.handle.net/10419/305966 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen. 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Introduction The Internet, which emerged with the development of information and communications technology (ICT), Received: Jan. 2, 2024; Revised: Feb. 16, 2024; Accepted: Feb. 23, 2024 † Corresponding author: Junhwan Mun E-mail: [email protected] is dramatically changing not only global industrial and economic growth but also the way people live (Commission, 2016). The global growth of online platform companies poses a significant threat to big tech companies. They have allowed online platforms to assume the roles of god-like gatekeepers, legislators, judges, and juries because of their enormous economic value and innovation (Cutolo et al., 2021); now is GLOBAL BUSINESS & FINANCE REVIEW, Volume. 29 Issue. 3 (APRIL 2024), 16-29 pISSN 1088-6931 / eISSN 2384-1648∣Https://doi.org/10.17549/gbfr.2024.29.3.16 ⓒ 2024 People and Global Business Association GLOBAL BUSINESS & FINANCE REVIEW www.gbfrjournal.org for financial sustainability and people-centered global business1) A nalysis of the Present and Future of the Korea Online Platfor m Regulation Using Latent Dirichlet Allocation J unhwan Mun† D epartment Data and Knowledge Service Engineering, Dankook University Gyeonggi-do, Korea A B S T R A C T Purpose: This study was conducted to provide a comprehensive understanding of online platform regulation in South Korea. It aims to illuminate key issues related to online platform regulation from 2017 to 2021, exploring the current state and future prospects. The primary goal is to foster social discourse on online platform regulation and to offer valuable insights for policymakers and academics. Design/methodology/approach: The methodology involved collecting articles from a large news database using keywords associated with online platform regulation. This data was analyzed using Latent Dirichlet Allocation (LDA) topic modeling. This technique is instrumental in identifying themes and patterns within large volumes of text data, facilitating the identification of significant themes and trends related to online platform regulation. Findings: The study unearthed a variety of themes. Among the most significant are the impact of the COVID-19 pandemic and its ramifications, political aspects, the roles of major Korean corporations (e.g., Naver and Kakao), the influence of global tech giants, the impact of news and online communities, technology and innovation, and social issues. These themes indicate that online platform regulation in Korea is influenced by a multitude of factors. Research limitations/implications: While this study offers diverse perspectives on online platform regulation within Korea, it has limitations. Reliance on data from a single news source may restrict the study's diversity and depth. Future research should employ a variety of news sources to provide a broader perspective on online platform regulation. Originality/value: This research makes a significant contribution to the academic study and policy formulation in the field by analyzing the key themes and trends related to online platform regulation over time. By exploring the complex aspects of online platform regulation, the study provides new insights for policymakers, researchers, and the general public. Keywords: Online platform, Platform regulation, News data, Topic modeling, Latent Dirichlet Allocation ⓒ Copyright: The Author(s). This is an Open Access journal distributed under the terms of the Creative Commons Attribution Non-Commercial License (https://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distribution , and reproduction in any medium, provided the original work is properly cited. Junhwan Mun 17 the time for change, and there are growing calls to regulate this powerful dominance. In particular, the transition to a non-face-to-face society owing to the COVID-19 outbreak in 2020 led to the explosive growth of online platform services (Yu, 2023). The transaction amount of vertical commerce platforms such as "Musinsa" (fashion), "Market Kurly" (food), and "Must It" (luxury) was 5,887.3 trillion in 2021, which is a 33.5% increase from the previous year (Korea, 2021b). According to PwC's "Global Top 100 companies by market capitalization," five out of 10 global companies in 2019 are big tech companies that operate platform businesses (PwC, 2019). Compared with 2009, when only Microsoft and Alphabet were involved, it can be seen that there is a rapid increase in the influence of online platform companies on the world. Korea's online shopping transaction amount is 17.5 trillion (Korea, 2021a). The reason for such significant economic value is that online platforms span various fields and have established "themselves as essential means, tools, and mediums" in our daily lives (Lee, 2021), with their influence expanding offline as well, thanks to the online-tooffline (O2O) business model adopted by several platforms. Digital markets, such as Internet platforms, have a winner-takes-all structure with high entry barriers and market concentration because of characteristics such as network effects, conversion costs, and economies of scale (Gawer and Cusumano, 2014; Judiciary, 2019; Walker, 2020). Therefore, countries worldwide have made efforts to enact laws and guidelines to prevent competition and consumer rights from being infringed by the anti-competitive behavior of related business operators, despite the economic utility and practical benefits of digital platforms (Forum, 2019). In South Korea, as online consumption increases in the aftermath of the long lasting COVID-19 pandemic, the controversy over unfair trade between online platforms and small offline businesses continues, and there is an emerging need for regulatory measures to protect them. Although the "Online Platform Intermediary Transactions Fairness Bill" has not been enacted in the National Assembly in Korea, a consensus has been reached between the ruling and opposition parties on platform regulation, and it is expected that the regulations will be applied to the IT industry as a result of an agreement between the Fair Trade Commission and the Korea Communications Commission. There are conflicting opinions about the Bill in Korea. Opinions in favor of protecting small offline businesses and those in favor of the online platform industry concerned about excessive regulation are in conflict (Cheong, 2021; Walker, 2020). More than half of the consumers oppose online platform regulations. The Consumer Awareness Survey on Online Platform Delivery Service Regulations published by the Korea Startup Forum in February 2021 revealed that 61.4% opposed online platform regulation 1) . Among the problems with online platforms, the frequently mentioned commission structure is only the tip of the iceberg (Cutolo et al., 2021). The fundamental problem is that vendors cannot compete freely on online platforms, and even if they release innovative products, platform companies can eventually gain a competitive advantage by offering their own products (Cutolo et al., 2021). This is because platform companies have data not only from vendors but also from consumers, which is advantageous for expanding various service models and allowing them to promote their own products first, through advertisements (Lee et al., 2022). The issue of unfair behavior due to the monopoly of data by such large platform companies is starting to draw attention as a social problem (Kim and Lee, 2021). In addition, the power of platform companies is strengthened by competitive strategies, such as M&A, zero pricing, typing, and predatory pricing (Kim et al., 2021). In response, some experts state that the problems of specific online platforms should not be generalized, others say that they should not be duplicated (Lee, 2021), and still others say that competitive strategies should not be misinterpreted (Kim et al., 2021). This is because objectively measuring the impact of platform company strategies on consumers 1) "Startup organizations" online platform regulation, question about the effect of protecting local commercial areas, Yonhap news, 2021.02.22. https://www.yna.co.kr/view/AKR202102220345000 17?input=1195m GLOBAL BUSINESS & FINANCE REVIEW, Volume. 29 Issue. 3 (APRIL 2024), 16-29 18 and industries is difficult. Therefore, the regulation of online platforms is complex (Akman, 2021; Colangelo and Zeno-Zencovich, 2016). Dealing with online platform issues requires a multipronged approach. This is because the issues change over time due to diverse stakeholders and services and their innovative nature (Kim, 2021). Platforms that fall under the category of online platforms are diverse. Korea's representative online platform services include open markets, delivery apps, lodging apps, riding apps, real estate, and used car information provision services. Considering these characteristics, regulations for platform companies should be established and operated for each common issue. Accordingly, this study examined issues related to online platform regulation from various perspectives and examines important issues that have emerged over time. The study period was from 2017 to 2021, when online platform regulations were recommended. The research method used was Latent Dirichlet Allocation (LDA), which is a text mining technique that collects news data with keywords related to online platform regulation. The purpose of this study was to systematically capture the social changes caused by online platform regulation and discover topics for social discussion. LDA, an exploratory research method, is suitable because online platforms have a wide range of services, and are subject to large changes over time. News data were selected as the subject of analysis in this study because news is a representative medium for understanding issues that have received attention from the public in a specific era. In addition, the collected data are vast and unstructured, and it is possible to extract and process useful information from unstructured or semi-structured text data based on natural language processing technology, as well as to understand the relationship between texts (Paranyushkin, 2011). This approach helps identify the current trends of online platform regulation over a short period and also aids in predicting future trends from a long-term perspective. This study raises the following research questions: Research Question 1. What are the major keywords concerning online platform regulation? Research Question 2. What are the main issues among these keywords? II. Review of Related Research A. Concept and Current Status of Online Platform Regulation Online platform regulation aims to protect consumers, platform vendors, and individual companies from unfair market competition (Commission, 2020). The Online Platform Intermediary Transactions Fairness Bill aims to regulate unfair trade practices and protect small and medium-sized enterprises (SMEs). Consequently, many European Union (EU) rules, for online platforms, with similar legislative purposes have been borrowed (Jang, 2021). For instance, the bill mandates platform companies to transparently disclose transaction terms to vendors and publish key contractual items to prevent disputes, such as the period, change, renewal, and termination of brokerage contracts; the content, period, and price of online platform brokerage services; and the commencement, limitation, suspension, change, etc., of brokerage services. However, there is criticism that currently proposed online platform regulationrelated laws do not specifically address the need for economic regulation, and a more thorough investigation is required because there is a risk that the laws can be applied in a uniform manner by generalizing the problems of specific online platforms, and it is difficult to avoid overlapping regulations (Lee, 2021). The scope of online platform regulation varies depending on how legislation defines an online platform. An online platform is defined as "Internet homepages, mobile applications, and equivalent electronic systems for the purpose of interaction such as transaction of goods or services and information exchange between two or more groups of users" in Article 2 of the Online Platform Intermediary Transactions Fairness Bill. However, online shopping malls that sell directly, social media with no transactions, and customer-to-customer (C2C) platforms that provide Junhwan Mun 19 second-hand prices between individuals are excluded. The Organization for Economic Co-operation and Development (OECD) defines an online platform as "a digital service in which two or more users (companies or individuals) interact with each other that are clearly distinct and interdependent online." In the United States and the EU, the subject of regulation differs according to law. Unlike the U.S., which is restricted to Google, Apple, Facebook, and Amazon (GAFA), the EU has a comprehensive online platform approach. The EU's online platform regulation law divides online platform operators into "online brokerage service providers" and "search engine operators" (Commission, 2020). The former refers to business operators in which direct transactions are made between users and consumers, while the latter is defined as digital service providers that provide a search term function (NARS, 2021). The current status of online platform regulation in the EU and the United States is as follows. First, the EU is the most active in regulating online platforms. This is to monitor the U.S., which dominates the online platform market, and to increase the competitiveness of companies in the EU (NARS, 2021). The EU enacted the platform-to-business (P2B) regulation on June 20, 2019, and implemented it in 2020. The Digital Services Acts (DSA) and the Digital Market Act (DMA), collectively referred to as the DSA package, have been proposed and are under discussion (Commission, 2020). The P2B Regulation was enacted because problems with platform conglomerates, such as opaque search rankings, emerged. This has a great impact on SMEs entering into the online platform business (Choi, 2021). This regulation regulates the tyranny of platform companies by targeting online intermediation services. DSA is classified into four types: brokerage services, hosting services, online platforms, and super-large online platforms. There is a differentiated regulatory method for each stage. Through this, it aims to improve the mechanism to effectively protect the basic rights of users and strengthen the public supervision of the platform. In addition, DMA aims to address the side effects of super-large online platforms by establishing standards for defining large-scale online platforms as "gatekeepers" (Choi, 2021). B. Literature Review on Online Platform Regulation The biggest characteristic of an online platform is that it is a multi-sided market (Evans and Schmalensee, 2017; Feld, 2019; Parker et al., 2016). A multi-sided market refers to a market in which two or more groups interact through a platform, and the value generated at this time is indirectly influenced by those outside the network. Therefore, defining the anti-competitive behavior of a platform cannot but involve the participants of the multi-sided platform market. Ballon and Van Heesvelde (2011) divide an online platform's main stakeholders into users and content developers. Platform operators are divided into four types: neutral, broker, enabler, and integrator platforms, according to the presence or absence of control over each stakeholder, and they argue that a differential regulatory approach is needed based on the degree of controllability. Among them, it is argued that stricter regulation is needed for the integrator platform, which controls most users and content providers. By contrast, Center (2019) emphasized that even if the social benefits of digital technology are enormous, measures to minimize the harm are necessary. Although it is true that automobiles have brought tremendous benefits in the past, traffic laws have significantly reduced the damage caused by automobiles. In Europe, where the market has already been virtually dominated by large online platforms in the United States, a strong pre-regulation method has recently been proposed (Commission, 2020). Germany and the UK have a common focus on the huge network effect in the digital market, with tipping, intermediation power, status as a gatekeeper, unbalanced bargaining power, data, and access rights issues as decisive competitive factors, arguing that some platforms cannot contest within the competitive mechanism of the market (Furman et al., 2019; Schweitzer et al., 2018). They also urged the amendment of competition GLOBAL BUSINESS & FINANCE REVIEW, Volume. 29 Issue. 3 (APRIL 2024), 16-29 20 laws to respond strongly to their abuses and to speed up the recovery from competition (Kerber and Australia, 2019). Some are concerned that the scope of application of online platform regulation is too wide and that regulatory uncertainty is growing. Online platform regulations can act inversely as a hindrance to the growth and innovation of domestic companies. We have often witnessed large-scale companies disappearing owing to market segmentation, and service and price differentiation, despite strong network effects (Belleflamme and Peitz, 2019; Evans and Schmalensee, 2007; Evans, 2017; Jullien et al., 2021). If the direction of online platform regulation is focused on the growth and development of the domestic industry, it can play an important role in strengthening the digital literacy of citizens and improving the quality of consumer consumption. In the long term, this will help the national economy by increasing opportunities in the labor market. In addition, as social participation channels diversify and social connectivity improves, startups are expected to increase. Platform companies should also continuously provide value and benefits so that merchants do not move to other platforms. However, such as not being aware of this fact, the problem of excessive fees charged to retailers continues to arise. Apple and Google receive 30% of revenue from the App Store, Etsy receives 20 cents per item, 5% of transaction cost, and payment commission, while YouTube receives 45% of advertising revenue (Cutolo et al., 2021). The platform seeks to exercise market dominance by increasing revenue. However, participants can leverage the resources provided by the platform to develop their ability to establish strategic positions and defend. For example, retailers can reduce their dependence on platforms through multi-homing, marketing using social networks, and diversification of products or channels (Pohle, 2020). III. Research Methods A. Data Collection Figure 1 shows the analysis procedure followed to answer the above research questions. First, we collected news related to online platforms from 2017 to November 10, 2021, in JoongAng Ilbo, Korea. To prevent keywords from being incorrectly reflected and omitted when searching for "online platform regulation" when collecting news data, "regulation" was used as a key keyword and additional words were combined to select keywords that fit the topic. The search terms were set to regulation (online or platform, Naver, or Kakao), and 3,9848 cases were collected. Only Naver and Kakao were included because they are Korea's representative big tech companies. As of June 2021, Kakao had 45.66 million mobile application users in the first half of 2021, which is higher than YouTube's 43.14 million. Naver ranks third at 41.06 million. Eighty-eight percent of the total population, which was 51.78 million in 2020, used online platforms. Among the 3,948 articles collected, those with different titles but with the same content were removed, resulting in 3,802 articles. LDA was performed using 3,184 articles through preprocessing. B. Data Preprocessing We examined the results after training the model several times during the preprocessing phase (Jun et al., 2014). Keywords such as "last year," "last month," "almost," "middle," "JoongAng Ilbo," "SoJoong," (the newspaper for children) "meantime," and "same" were treated as non-words. Subsequently, only nouns were extracted, and punctuation marks, the reporters' email addresses, and Chinese characters and English content were removed. Looking at the data trend by period, as shown in Figure 2, it can be seen that the related discussions were concentrated from 2020, when the plan to implement the Online Platform Intermediary Transaction Fairness Bill was announced. Junhwan Mun 21 C. LDA Topic Modeling For topics that are dynamic and change over time, such as online platforms, topic modeling with LDA is effective. LDA topic modeling is a probabilistic technique that weaves words used in a vast amount of data by topic. This is beneficial for big data analysis in that an entire document can be analyzed without a researcher labeling the data. The main assumption of LDA topic modeling is that topics exist before a document is written, from which words are extracted and written (Blei, 2012). Thus, LDA topic modeling is a method for identifying unobserved topics through an observed variable in a document. The following equation illustrates the concept of LDA topic modeling.     ∏   ∣  ∏   ∣  ∏   ∣    ∣   (1) To designate the n th word in document d , a topic is first assigned, and then the position of the word is determined according to the distribution of the topic. This is also well expressed in the equation, where  is the n th word in document d ,  is the word distribution of the topic,  is the topic of the n th word in document d,  is a parameter that determines the distribution of topics, and  is the distribution of words in topics. When determining the number of topics, researchers refer to perplexity and coherence indices as important parameters (Chang et al., 2009; Newman et al., 2010). Perplexity refers to the predictive performance of a given model. Coherence indicates the consistency of the derived topic. Therefore, the lower the degree of confusion and the higher the degree of cohesion, the better are the model results. As shown in Figure 3, 35 topics were selected in the model used in this study (coherence:0.6569, perplexity:1244.1445). Data Collection ▷ Data Preprocessing ▷ LDA Topic Modeling Keyword: "Regulation" and (Online Platform or Online or Platform or Naver or Kakao) : 2017 ~ 2021. 11. 10 : Total 3,948 articles 1) Remove duplicate articles Remove articles with different titles but the same content: 3,802 articles 2) Preprocessing : 3,184 articles 1) Keyword Analysis 2) Topic Analysis 3) Category classification Figure 1. Overall procedure of analysis Figure 2. Amount of news data per period Figure 3. Coherence and perplexity score according to the number of topics GLOBAL BUSINESS & FINANCE REVIEW, Volume. 29 Issue. 3 (APRIL 2024), 16-29 22 IV. Analysis and Results A. Results of Frequency Analysis Table 1 summarizes the frequency of each word to identify the words that appear most frequently in relation to online platform regulation in the study data. First, words such as "service," "online," "data," "internet," "digital," and "system" that reveal the characteristics of online platforms appeared. Next, "Kakao," the core company of Korea's online platform, was ranked third, and "Naver" took fourth place. Words such as "consumer," "stakeholder," "businessman," and "investor," representing the various stakeholders of an online platform appeared, and the words "President" and "Committee" related to the government regulating online platforms also emerged. In addition, the keyword "COVID-19," an assertion reflecting the COVID-19 pandemic, and "bitcoin," "startup," and "exchange," which represent innovation and technological development, appeared frequently. B. Results of LDA Topic Modeling Table 2 shows the results of topic modeling with the derived and labeled top 10 keywords. For example, in the case of topic 1, the topic was labeled as local politics based on the words "president," "democratic party," "Moon Jae In," "chairperson," "the Blue House," "committee," "Republic of Korea," etc. The main keywords of topic 2 were "automobiles," "electric vehicles," "Hyundai Motor," "Semiconductors," "batteries," and "eco-friendly" and was labeled automobiles. A total of 21 topics were derived by classifying topics closely related to online platform regulation. C. Results of the Major Themes from LDA Topics Table 3 shows the final analysis results classified into seven themes. The generated topics can be divided into themes such as COVID-19, politics, Naver and Kakao, global big tech companies, news and online communities, technology and innovation, and social issues. In this study, the top 21 out of the 35 topics that could be classified into seven themes were selected, and the connotations of each theme in our society were examined. The first major theme was defined as COVID-19. Online platforms have become more established as most of our daily lives have been shifted online owing to COVID-19. This phenomenon is well demonstrated in the results of this study. Two of the 35 topics were related to online platforms. One is a topic related to COVID-19 and the medical system (Topic 9), and the other is about the self-employed and working conditions (topic 35). The two topics are labeled No. Word Freq. No. Word Freq. 1 Service 5877 11 Global 1683 2 Online 3993 12 Bitcoin 1671 3 Kakao 3530 13 Real Estate 1662 4 Naver 2876 14 President 1631 5 Data 2520 15 Committee 1630 6 Internet 2453 16 Business 1537 7 COVID-19 2312 17 Startup 1494 8 Digital 1952 18 System 1434 9 Consumer 1913 19 Stock Exchange 1417 10 Persons concerned 1757 20 Investor 1361 Table 1. Results of the main keywords Junhwan Mun 23 differently because the top 10 keywords for both are different. Topic 9 includes medical-related words such as "COVID-19," "virus," "online," "infectious disease," "digital," "post-," "treatment," "mask," "expert," and "medical staff." A few randomly selected articles based on this topic are: "Do I have to go to the hospital myself?" "The 20-year cause" "blown away by the coronavirus," "K preventive measures ridiculed and Servant Syndrome," and "These are criticisms of the medical field related to COVID-19, and the Topic number Topic label Top 10 Keywords 1 Fintech Services, Consumers, Fees, Fintech, Naver, Online, Mobile, Operators, Systems, Commerce 2 Online education System, Digital, Smart, Online, Artificial Intelligence, Project, Ministry of Education, Service, Global, University 3 Local media Media, Naver, News Media, Used Car, Democracy, Committee, Online, User, Internet, Macro 4 Local Online Platform Kakao, Naver, Kakao Talk, Kim Bum-soo, Mobility, Subsidiary, Workers, Platforms, Games, Users 6 Automobiles Automobiles, electric vehicles, Hyundai Motor, Semiconductors, Batteries, Samsung Electronics, Global, eco-friendly, Kia Motors, Vice Chairman 7Naver & Fair Trade Commission Naver, Fair Trade Commission, Founder, Fair Trade Commission, Chairman, Affiliates, Trade Act, Same Person, Lee Hae-jin, Unfair Trade Commission 8 Online shopping Online, Consumer, Shopping Mall, Department Store, Convenience Store, E-Mart, Brand, Offline, Official, Seoul. 9COVID-19 & Medical system COVID-19, Virus, Online, Infectious Disease, Digital, Post, Treatment, Masks, Experts, Medical staff 13 Bitcoin Bitcoin, Exchange, Blockchain, Investor, Digital, DFY, Central Bank, Project, Service 14 Local politics President, Democratic Party, Moon Jae In, Chairperson, the Blue House, Committee, Republic of Korea, Olympics, Representative of a Party, Park Geun Hye 15 Vietnam Service, Global, Mobile, Soft, Competitive, Business, Vietnam, Southeast Asia, Content, Related Parties 17 OTT Business operators, Amendments, Netflix, Korea, YouTube, Services, Internet, Global, Telecommunications Companies, Committees 19 China & Startup Startup, Alibaba, Tencent, Unicorn, Founder, Global, Indonesia, Singapore, Internet, Asia. 23 Environment Energy, Fine Dust, Eco-friendly, Private Education, Gas Station, Solar Power, Parents, Greenhouse Gas, Nuclear Power, Online. 24 American Media Trump, President, Facebook, Twitter, Media, Biden, Travel Agency, Russia, Online, Donald 25 Kakao Bank Internet, Kakao, Committee, Major Shareholders, Guidelines, Officials, Capital, Researchers, Amendment, First Half of the Year 27 TADA & Mobility Services, Mobility, Automobiles, Startups, Rental Cars, Kakao, Business Operators, officials, Ministry of Land, Infrastructure and Transport, Amendments 28 Online community YouTube, Internet, Website, Online, Community, Netizens, Programs, Real-time, Video, Officials 33 Adolescents Digital, Youth, Online, Item, Victim, User, Committee, Website, Sex Crime, Pornography 34 Global Big Tech Company Facebook, Amazon, Commission, Consumer, Store, Antitrust, Fee, Global, Report, Service 35 COVID-19 & Working conditions COVID-19, Self-employed, Virus, Infectious Disease, Online, Difficulty, Association, Telecommuting, Subsidies, Voice Table 2. LDA topic modeling results