What Are Social Media Algorithms? Complete Guide for 2026

Billy Odell Tucker-Robinson Founder & Host — Banking With Billy Network • Intelligence Network • Data Science • AI Research • World News
Published: 2026-10-02T15:40:36.028Z • Permanent link

Facebook's algorithmic overhaul in 2022 marked a significant turning point for the social media industry, and now ByteDance, the parent company of TikTok, is facing scrutiny over its own algorithmic practices. Recent studies suggest that TikTok's algorithm prioritizes content from accounts that are most engaging to its users, regardless of their geographical location or demographics. This approach has raised concerns about the spread of misinformation and the homogenization of online content.

The issue has sparked a heated debate among researchers and policymakers, with some arguing that TikTok's algorithm is too opaque and lacks transparency. For instance, a report by the non-profit organization, Social Rails, has highlighted the lack of clarity surrounding TikTok's algorithmic decision-making processes. The report notes that the platform's algorithm is based on a complex set of factors, including user behavior, engagement metrics, and even device type. These factors are used to determine the order in which content is displayed to users, with the ultimate goal of maximizing engagement and user retention.

Mark Zuckerberg, Facebook's CEO, has been vocal about the need for greater transparency in algorithmic decision-making processes. In a recent interview with CNBC, Zuckerberg emphasized the importance of understanding how social media algorithms work, citing concerns about the spread of misinformation and the erosion of trust in online platforms. By contrast, Shou Zi Chew, the CEO of TikTok, has been relatively tight-lipped about the company's algorithmic practices, fueling speculation about the true nature of the platform's content prioritization.

TikTok's algorithmic practices have significant implications for the research community, which is increasingly reliant on social media data to inform its studies. For instance, a recent study published in the journal Science found that social media algorithms can amplify existing biases and reinforce social and cultural divisions. As such, researchers are now calling for greater transparency and accountability in algorithmic decision-making processes. Companies like TikTok and Facebook are also facing increasing pressure from regulators, who are seeking to establish clearer guidelines for the use of user data in algorithmic decision-making.

The implications of TikTok's algorithmic practices extend far beyond the social media industry, however. The platform's ability to shape public opinion and influence user behavior has significant implications for markets, policymakers, and even global politics. For instance, a study by the University of Oxford found that social media algorithms can have a profound impact on public opinion, with some studies suggesting that algorithm-driven content can be up to 30% more persuasive than traditional forms of communication. As such, companies like TikTok and Facebook are facing increasing scrutiny from regulators and policymakers, who are seeking to establish clearer guidelines for the use of social media data in algorithmic decision-making.

The issue of algorithmic transparency is not new, however. In the early 2000s, researchers began to explore the use of algorithmic decision-making processes in social media platforms. For instance, a study published in the journal Cyberpsychology, Behavior, and Social Networking found that Facebook's News Feed algorithm was designed to prioritize content that was most engaging to users, regardless of its relevance or accuracy. This approach was seen as a key factor in the spread of misinformation and the erosion of trust in online platforms.