Social Media Algorithms Contributes to Isolation
Social media platforms were designed to maximize engagement, not social harmony. While these platforms offer undeniable benefits—connection, education, and awareness—they also carry structural flaws that unintentionally fuel discrimination against minorities, particularly through the normalization of repeated content.
At the core of this issue lies a simple psychological reality: what people see repeatedly begins to feel normal, acceptable, and representative of reality. This is not speculation; decades of behavioral science confirm that repeated exposure shapes belief, perception, and behavior. Social media algorithms exploit this mechanism by design—showing users more of what they have already seen, regardless of the social consequences.
Normalization Through Repetition
When a user clicks on a harmless video—such as dancing, animal rescues, or science inventions—the platform immediately suggests similar content. This mechanism is neutral in theory but dangerous in practice when applied to harmful or discriminatory material.
If someone, even once and out of curiosity, watches:
• A video portraying Minorities as threats
• Content suggesting immigrants are stealing jobs
• Footage framing certain Race, Ethnicity, Skin Color as criminals
• Videos glorifying violence, bullying, or intimidation
…the algorithm often responds by delivering more of the same.
Repeated exposure does not simply inform—it conditions. Over time, the viewer begins to perceive these narratives as widespread, normal, and justified. This is how anti-Muslim bigotry, anti-minority sentiment, and broader discriminatory narratives become normalized, even among individuals who did not initially hold those views.
A Global Cycle of Distortion
This algorithmic distortion operates in all directions and across borders. In extremist environments, individuals may watch one or two videos portraying the West as immoral, violent, or hostile to religion. Algorithms then reinforce this worldview, creating a perception that the West is universally corrupt and hostile—fueling resentment and radicalization. In Western societies, a single click on content criticizing immigration or minorities can trigger a cascade of similar videos, reinforcing the belief that minorities are threats to economic stability, security, or cultural identity. In both cases, the user is not exposed to balancing perspectives, positive examples, or contextual explanations that could reduce fear or hostility. The result is a narrowed worldview shaped not by reality, but by algorithmic repetition.
Peer Pressure, Social Learning & Digital Influence
Research in psychology and sociology consistently shows that people are strongly influenced by perceived social norms. Studies indicate that:
• Repeated exposure increases acceptance, even of extreme or false ideas.
• Peer-like reinforcement, such as likes, shares, and repeated visibility, strengthens belief.
• Social learning theory confirms that people adopt behaviors and attitudes they see modeled frequently.
On social media, algorithms function as invisible peers, constantly reinforcing certain narratives. When discriminatory content appears repeatedly, it sends a silent message: this is common, this is acceptable, this is normal.
This dynamic has been observed in real-world harm:
• Online communities normalizing hate speech before offline violence
• Repeated exposure to violent content desensitizing viewers
• Extremist attackers citing online content ecosystems as part of their ideological reinforcement
Freemuslim’s Position: Alarm Without Accusation
Freemuslim and its leadership view this issue with deep alarm but without assigning malicious intent. Social media platforms may not aim to promote discrimination, but their systems unintentionally reward it through engagement-based design. Normalization does not make harmful ideas less dangerous—it makes them more socially acceptable. When hate feels ordinary, resistance weakens. When violence feels common, empathy erodes. When discrimination feels justified, society fractures.
This harms minorities, women, children, religious affiliations and ultimately humanity as a whole—in every country, across every culture.
A Call for Structural Reform, Not Censorship
Freemuslim calls for root-level changes in how social media platforms manage content recommendation:
1. Stronger filtering of discriminatory, violent, and harmful content, even when it is implied rather than explicitly stated.
2. Limits on repetitive exposure to content involving violence, hate, bullying, theft, or harmful behavior—regardless of user curiosity.
3. Contextual differentiation, recognizing that educational content (e.g., discussions of weapons or crime prevention) is not the same as glorification.
4. Algorithmic balance, where exposure to harmful narratives is countered with opposing, educational, or humanizing perspectives.
5. Shared responsibility, where not only creators but also viewer interaction patterns are considered in limiting harmful normalization loops.
If repeated exposure can shape the brain—and science confirms that it can—then platforms have an ethical obligation to reduce harmful repetition.
Conclusion: Technology Shapes Society
Social media does not merely reflect society—it actively shapes it. What is amplified becomes accepted. What is repeated becomes normalized.
Freemuslim believes that technology must serve humanity, not divide it. Without thoughtful reform, algorithmic systems will continue to unintentionally fuel discrimination, deepen division, and normalize harm. This is not a call to silence voices—but a call to design platforms that protect human dignity.
