Facebook’s algorithm for ranking and displaying comments has evolved over time in an effort to show users the most useful and relevant conversations. There are a few key reasons why Facebook may now be showing only a subset of comments on a given post:
Reducing low-quality comments
Facebook has made an effort to reduce the visibility of comments that may be considered abusive, spam, or otherwise low-quality. Their automated systems look for certain signals like repetition, keywords, source domains, etc. to identify comments that are not contributing meaningful discussion. By limiting the visibility of these types of comments, Facebook aims to improve the overall comment experience.
Promoting engagement
Facebook also wants to promote and highlight comments that are likely to be the most interesting and lead to further engagement. Things like comments from the original poster, comments with high reaction counts, and back-and-forth discussion threads may be ranked higher. This helps bubble up the most active conversations.
Prioritizing relevance
Relevance to the original post is also a key ranking factor for Facebook. Comments that directly address the content and ideas of the post tend to be ranked higher than generic comments. The goal is to show comments that are on-topic for the discussion.
Limiting comment overload
On posts with extremely high comment volumes, Facebook will typically show only a portion of the comments initially. This prevents the page from becoming overloaded and helps focus the discussion on the most relevant conversations. Users can click “View more comments” to expand as desired.
Personalization
The comments that are shown to a user are also personalized based on signals like pages they’ve interacted with, posts they’ve commented on, and contacts they engage with. The goal is to show each user the comments most relevant to them.
Moderation
Page admins and moderators can also limit the visibility of comments manually. They may choose to hide certain comments that violate guidelines or are irrelevant without fully removing them.
Reducing polarized and misleading discussions
Facebook has faced criticism that its platforms can sometimes promote polarizing and divisive comment discussions. The algorithmic ranking of comments is part of their strategy to highlight productive discourse and limit the reach of divisive conversations.
Promoting ideologically diverse comments
Related to the goal of reducing polarized discussions, Facebook says its systems aim to promote ideologically diverse conversations in comments. This means comments from different perspectives, not just the most predominant views, are mixed into rankings.
Combating coordinated manipulation attempts
Facebook is also using comment rankings to detect and limit coordinated efforts to manipulate public discourse, such as state-sponsored propaganda campaigns or commercial spam rings. By analyzing comment patterns and connections, they aim to flag and demote inauthentic activity.
Compliance with local laws
As Facebook operates in many different countries, they sometimes adjust comment visibility to comply with local laws regarding speech and expression. For example, certain types of comments may be limited in some regions due to moderation laws.
User controls and accessibility
While Facebook’s algorithm drives the default ranking and presentation of comments, users have some ability to customize what they see. For example, the ability to sort comments chronologically or by engagement gives users more control. There are also accessibility features like screen reader support.
Ongoing algorithm refinement
Facebook is continually making changes to improve their comment ranking systems. Over time they’ve incorporated more signals, user feedback, and machine learning techniques. The goal is to show the most relevant discussions to each user on every post.
Criticisms and controversies
Facebook’s approach to comment ranking has drawn criticism from some users:
- Accusations of political bias and “censorship” of particular viewpoints
- Lack of full transparency about what factors influence rankings
- Perception that only majority opinions are highlighted
- Complaints that chronological ranking has been removed as the default
Facebook maintains that its systems aim to be neutral and personalized without political or ideological bias. But the company acknowledges ongoing challenges around comment rankings, and the need for more accountability. Striking the right balance remains an active area of discussion.
The future of comment ranking
Looking ahead, Facebook is likely to keep innovating with its comment algorithms:
- More advanced NLP and machine learning to understand comment sentiment, tone, and semantics
- Stronger methods to detect and demote inauthentic engagement
- Integrating user feedback through polls, surveys, and transparent controls
- Potential shift back towards more chronological commenting in some areas
- Adding more signals specific to local cultural context and online norms
Facebook’s sheer scale – with billions of users worldwide – makes comment ranking an incredibly complex challenge. The company still has much progress to make in terms of earning user trust and balancing open discussion with mitigating abuse.
Conclusion
Facebook’s approach to ranking and filtering comments on posts stems from a range of factors: curbing low-quality content, highlighting relevance and engagement, personalization, and compliance. It remains an evolving effort to promote meaningful discussions and limit toxicity. Controversies persist around issues of neutrality, transparency, diversity of perspectives, and user control. Facebook will likely continue updating its comment algorithms to address these complex and critical issues.
| Year | Key Changes to Comment Ranking Algorithm |
|---|---|
| 2009 | Initial comment ranking based on factors like engagement and connection to poster |
| 2012 | New NLP and machine learning techniques to assess comment quality |
| 2016 | Expanded abuse detection capabilities and demotion of low-quality comments |
| 2018 | Algorithm tweaks to prioritize local relevance of comments |
| 2021 | Stronger detection and limitation of toxic and misleading information |