Abstract
Rating reviews in the game industry aim to enhance the protection of young users, promote game ethics, and prevent negative use of it as a gambling but recent studies and public opinions have reported that the current rating system in South Korea is excessively regulative. To address this issue, this study was conducted to redesign the public game rating system on the Game Ratings and Administration Committee (GRAC) for the public data usage based on the comparison with other better structured media rating systems. The redesigned system utilized a parsing technique to easily access specific data or items, and a Jsoup library was utilized in the Java environment. The system consists of a URL collection module, connection module, detailed collection module, and storage module. If a user requests information from a game rating database through the proposed system, the requested information is arranged sequentially and provided to the user in XML and JSON forms. The designed and implemented collection data were comparatively inclusive and structural to satisfy the public for the better and easier public data usage. This study is expected to help build an environment where game users can obtain information both easily and correctly, and it will eventually lead to a better understanding of the current game industry in South Korea and its clear way to go.
1. Introduction
The statistical data on a white paper published by the Korea Creative Content Agency in 2019 indicated that the South Korean digital game industry has shown a gradual growth since 2009 as depicted in Figure 1 [1]. Just when people’s interest in games has increased and the game industry accomplishes good results at home and abroad, the regulatory review procedures, however, impeding the growth of the game industry in South Korea. According to Article 21 of the Game Industry Promotion Act, those who intends to create or distribute a new digital game shall go through the game classification system and receive a rating from the Committee [2]. Rating reviews aim to enhance the protection of young users, promote game ethics, and prevent negative use of it as gambling but recent studies and public opinions have reported that rating reviews are excessively regulative [3–5].
The Game Ratings and Administration Committee (GRAC) was launched in response to the controversy over whether the game “The Sea Story” was a gamble or not in 2006 as gambling is an illegal act in South Korea [6]. Since then, the GRAC builds the rating system to inform the users of the nature of the game. However, it is a complicated process to go through the rating system and it is more difficult to receive a pass. In addition, the GRAC suddenly charges high fees for the review process.
In 2019, the GRAC forced more regulations for indie games, test version games, and flash games that were published through the Internet. They have forced legal orders, thus, game developers have to go through the rating system before they publish the new game title to the game platforms including the zuzunza.com [7]. In addition, voluntary ratings were implemented to relieve regulation of the reviews. However, as shown in Table 1, the monitoring group for voluntary rating is composed of persons who have a poor understanding of digital games including job-discontinued women and disabled people which led to controversy on the lack of fairness and professionalism on the rating system [8–10]. This can result in the stoppage of a game service caused by wrong judgments from the nonprofessional groups and it makes a critical issue for the growing game industry [11]. Also, public data aims at “improving the quality of life and national economy by promoting people’s use of data owned and managed by a public institution” [12] and the GRAC belongs to a public institution and its game rating service is included in the public data.
Amid this controversy, this study was conducted to analyse and redesign the game rating system and its public data provided by the GRAC. This study is expected to help build an environment where game users can obtain information on the digital games both easily and correctly, which will eventually lead to a better understanding of the current game industry in South Korea and its clear way to go.
2. Literature Review
In other countries, research on the validity of game rating from a user’s perspective has been continuously conducted as well as on the role of parents in rating their children’s right to the use of games [13–16]. In South Korea, most studies related to rating classifications are conducted from sociological and legal perspectives but the studies from an engineering perspective are insufficient to verify the validity of the rating review system [17–20]. Thus, this study was conducted to analyse both types and contents of game classification and the ways in which the data is delivered to the public through the GRAC website from an engineering perspective.
First, the GRAC provides information on games in a form of open API (application programming interface) based on the public data policy as shown in Table 2. The list of contents is the variables and description of information that can be received through the GRAC API [21].
The game review data are very limited because they simply enumerate the results of game ratings as shown in Figure 2 and Table 3. The information regarding the game content and the reasons for which the game has received the given rating is insufficient. On the other hand, an open API shown in Table 4 depicts a movie rating provided by the Korea Media Rating Board (KMRB) that includes the results of ratings as well as additional information on the movie such as synopsis and lead role\ and provides reasons for the ratings [22]. Public data that allow people to check information in more detail can be used to satisfy the people’s rights to know and can be used for application service aiming at providing information on movies.
This comparison clearly indicates that the GRAC rating system needs to provide more information just like an open API that provides a movie rating system. People can check information and reviews on games by browsing through their titles and rating number on the rating decision check page found on the GRAC website.
3. Research Methodology
The entire process in which this study designed and implemented a system is shown in Figure 3. In order to improve the game and rating system on the GRAC’s website, firstly this study drew the wider range of items that users can tap on the website for their search. For this, this study made a comparison with the well-designed website from the Korea Media Rating Board (KMRB). A database where the data collection and classification are performed is built to provide users with extended public data for game rating.
4. Analysis of the Rating System and Interface by the Game Ratings and Administration Committee
The GRAC provides game rating data which are distributed through its website. People can check the information on games on the page of “a decision on rating” that allows users to understand the reason why the decision on rating of games was made as shown in Figure 4 [23]. The website also provides the links that moves to pages related to games and rating reviews that include “detailed information on games,” “a written decision,” “rating history,” and “present condition of the acquisition of overseas grade.”
The “detailed information on games” page allows users to check the detailed information on games that have requested a rating review as shown in Figure 5. Users can move to the relevant pages through the hyperlink on the game titles displayed on the “check for a decision on rating.” Users can check each item that includes the basic information on games such as “genre” and “nationality.” Users can also check for the basic information on ratings, for example, the “date of rating” and the “rating number.” According to the items on the relevant pages, the summary of the description and sample data can be obtained as shown in Table 5.
The “a written decision on game rating” page allows users to check a decision on rating of games that have requested rating reviews as shown in Figure 6. The content of a decision on games that requested rating includes the reason for the rating, a description of the game in one sentence, and the information on game contents. In the item of “indication of content information,” sensationality, violence, fear, unsuitability of languages, drugs, crime, and speculation are indicated based on the standard for consideration of ratings in the relevant studies.
Users can collect data on the page of “a written decision on games.” The summary of descriptions and sample data according to the items on the relevant pages can be obtained as shown in Table 6.
In order to improve the GRAC’s rating and information system, the game information items were derived based on “detailed information on games” page and the “a written decision on game rating” page that the GRAC website provides to the public as shown in Table 7.
5. Results
5.1. Extending on Game and Rating Information Items
After making a comparison with KMRB, this study drew the items that are needed to be improved from the page of “detailed information on games” and “a written decision on game rating” as shown in Table 8. The relevant items can be extracted from the GRAC database that contains the information on games and can be collected from the GRAC’s website. This redesigned and extended data base can allow users to check the information on game rating reviews more clearly and prepare a foundation that can be used in analysing and visualizing big data as shown in Table 8.
5.2. Designing and Implementing the Public Data Collection System
Then, this study designed and implemented a system that collects game rating data to provide users. The collection system was built based on the working environment as shown in Table 9. A parsing technique was used to easily access specific data or items and a Jsoup library was utilized in the Java environment. Jsoup is a library that enables users to easily find or extract data that they go by using a DOM search or a CSS selector. It can also implement the collection process by accessing a web page with a simple code. Jsoup allows users to make the analysis and access both effective and ineffective tags provided in a tree structure approach [24].
The system was designed to collect rating data from GRAC’s homepage as shown in Figure 7. The system consists of a URL collection module, connection module, detailed collection module, and storage module. The scheduler controlled the requests and modules.
The system collected detailed page URLs of each game and then verified whether the data exists in the relevant URLs. Then, the detailed page URL of each game was accessed to collect the rating data and store them in the database to build the data for game rating. Then, the system determined the state on whether data were stored normally by a scheduler, the time when the collection was done, and the time when storage was completed. Table 10 shows the results of data collection through the system. The collected data for game rating amounted to a total of 80,180 from May 12, 2020 to May 15, 2020 as shown in Table 10.
If a user requests information from a game rating database built through the proposed collection system, a preindexed dataset delivers the user’s requested data. The requested data are arranged sequentially based on their IDs and provided to the users in XML and JSON forms as shown in Figure 8.
(a)
(b)
In order to prove the utilization of the extended result data through the redesigned system in this paper, a comparison was made with other rating systems of movies. First, the preexisting GRAC rating system presents fragmentary items such as the game name, the decided rate, and the rating institution. On the other hand, the proposed extended data shows detailed information on the game’s genre, platform, descriptions, and the reasons for the review, sensationality, and violence as shown in Table 11. Thus, the extended data can be used as the basis for analysing the ratings. Second, it can be seen that the proposed game rating system is comparatively inclusive and structural enough to satisfy the public for the better and easier public data usage as shown in Table 12.
6. Discussion
After analysing the current system of the GRAC, the information provided to the public are very limited compared to other media rating system such as movies. Thus, this study first drew the items to be added for better understanding and fair rating system, and secondly designed a data collection system tailoring to the extended public classification data. The designed and implemented collection system successfully built the expanded public data provision foundation and was comparatively inclusive and structural to satisfy the public for the better and easier public data usage.
7. Conclusion
As the game industry and its users are rapidly expanding in South Korea, the public needs to check and gain the information about the games are also increasing. Unlike rating agencies in other countries that are comprised of private institutions, the GRAC in South Korea serves as a public institution [25]. Korean public institutions have a legal obligation to disclose the data that they held so the rating system needs to be thoroughly examined to strengthen fairness and the public’s right to know [26]. To properly perform this obligation, the entity must provide specific classification information including the research results, rather than just formal disclosure [27]. Thus, this paper was conducted to redesign the game rating system that the GRAC currently provides to make it a proper and fair rating system.
Further studies on expanding to big data analysis methods such as clustering and factor analysis will be conducted to predict the time of deliberation of games. Recently, research such as performance analysis of ML models for game grade prediction has been conducted [28]. This study will be the basis for expanding research to artificial intelligence or machine learning for game grade classification. In addition, the advanced big data analysis will be considered by utilizing ICT technologies such as machine learning and artificial intelligence.
Data Availability
The data used to support the findings of this study are available from the corresponding author upon request.
Conflicts of Interest
The authors declare that they have no conflicts of interest.
Authors’ Contributions
Conceptualization was done by K.-H.S.; data analysis was done by K.-H.S.; data curation was done by K.-H.S.; original draft preparation was done by K.-H.S. and K.-J.Y.; review and editing was done by K.-J.Y. All authors have read and agreed to the published version of the manuscript.
Acknowledgments
This research was supported by Ministry of Culture, Sports and Tourism and Korea Creative Content Agency (project number: R2020040243). This work was also supported by the Gachon University Research Fund of 2020 (GCU-202008460010), excerpt submitted thesis by HoSeong Kang for Master’s degree, University of Gachon, Republic of Korea, in 2020.