Naver Self-Regulation Committee 2nd Meeting... Discussion on Measures to Prevent 'Dark Patterns'

Naver announced on the 28th that it held the 2nd regular meeting of the 'Naver User Protection and Self-Regulation Committee (hereinafter referred to as the Naver Self-Regulation Committee)' and discussed measures to prevent dark patterns. Dark patterns refer to online screen layouts designed to induce users into irrational spending or misconceptions.

The meeting was attended by all members of the Self-Regulation Committee, including Kwon Heon-young, professor at Korea University Graduate School of Information Security and chairman of the Naver Self-Regulation Committee, as well as Naver's Park Woo-sung, Forward Lab lead, Kim Sung-kyu, Commerce Partnership & Operations Team leader, and Son Ji-yoon, head of policy strategy. Naver Forward Lab is Naver's user innovation experience research organization that considers operational directions to enhance users' service experience.

Naver Headquarters in Seongnam, Gyeonggi. Photo by Jinhyung Kang aymsdream@

Park Woo-sung, Forward Lab lead, introduced Naver's 'Company-wide Training for Dark Pattern Prevention' to the committee. This training focuses on four core principles aimed at respecting users' autonomy and providing trustworthy services: ▲Helping users make their own judgments ▲Not intentionally causing users to give up ▲Providing unbiased and complete information ▲Not pressuring users.

Kim Sung-kyu, Commerce Partnership & Operations Team leader, introduced Naver's user protection activities, including efforts to combat fake reviews. He explained efforts to respond to increasingly sophisticated abuse (view count manipulation) and plans to establish a monitoring system for review agency platforms. To sanction fake reviews, Naver takes measures such as ▲Issuing warnings and suspending accounts upon detection of fake reviews ▲Operating a review cleansing system and responding by blinding reviews suspected of abuse.

The Naver Self-Regulation Committee suggested opinions for fostering a healthy platform ecosystem, including ▲Checking new Naver services through a 'Dark Pattern Checklist' ▲Strengthening seller responsibility for review manipulation acts ▲Continuous investment in AI-based detection technologies.

The Dark Pattern Checklist is a guideline for service planning and development personnel to pre-check services when launching new services to enhance user satisfaction. It is composed from the perspective of content writing to ensure linguistic accuracy by avoiding usability issues and negative expressions to improve service utility and user satisfaction. The analysis results of the Dark Pattern Checklist will be included in the Self-Regulation Committee report to be released in the first half of 2024.

Additionally, the committee recommended strengthening seller responsibility to prevent user harm caused by fake reviews. For example, if a seller conducts a review event, it emphasized the need for enhanced user protection policies, such as more clearly disclosing whether compensation is involved at the top of the event page.

The committee also proposed continuous technological investment for the advancement of the 'Review Cleansing System' and the development of fake review detection models through AI learning. The review cleansing system applied to Naver Shopping reviews is a big data-based system that immediately stops displaying reviews when abnormal patterns such as advertising reviews are detected.

Chairman Kwon said, "We will measure user satisfaction according to dark pattern prevention activities and fake review policies and strive to establish Naver's efforts as a global best practice."

This content was produced with the assistance of AI translation services.