Valve has introduced a new feature on Steam aimed at improving the relevance of user reviews. This update, which is now enabled by default, introduces an auto-filter system designed to prioritize reviews that are most helpful for potential buyers.
Specifically, it targets “humorous but unhelpful” content, such as jokes, memes, ASCII art, and overly brief one-word reviews, by relegating them behind more substantive feedback on the store page.
According to Valve’s blog post, this system is intended to refine the sorting of reviews to better assist players in making informed purchasing decisions. The filter is automatically activated but can be toggled off if users prefer to see all types of reviews.
This adjustment reflects Valve’s intent to enhance the quality of review information available to potential buyers while maintaining the option for users who enjoy less conventional reviews.
While Valve acknowledges the entertainment value of humorous reviews for current players, it argues that such content often lacks practical utility for prospective buyers.
The company notes that while games that inspire playful reviews may be doing something right, there is also a risk of misleading or irrelevant feedback, particularly when poor games receive similar treatment. As a result, these unhelpful reviews will be moved down the page to make way for more useful insights.
The update raises questions about how it will handle negative reviews, particularly those resulting from review bombing. Valve has not directly addressed this issue, but it assures that the helpfulness filter will not discriminate based on the positivity or negativity of reviews.
This is exemplified by the situation with “Earth Defense Force 6,” where negative reviews related to an Epic Games account requirement are prominent, highlighting the ongoing debate about the impact of such filters on protest reviews.
Finally, Valve is aware that this new system is still evolving and acknowledges the possibility of legitimate reviews being mistakenly flagged as unhelpful. The company emphasizes that it is prioritizing easily identifiable unhelpful reviews and plans to continuously refine the process. As the system matures, it aims to strike a balance between filtering out non-informative content and preserving valuable user feedback.
