In recent years, social media has reshaped individual and collective behavior through algorithms and quantified visibility, becoming an amplifier of conformity. This study analyzes how social media exacerbates the herd mentality from both economic and sociological perspectives. This article identifies two core mechanisms. On the one hand, algorithmic recommendation, exemplified by personalized recommendations, is deeply integrated with the information industry, transforming how information is generated and disseminated. While this has a positive effect of increasing the efficiency of information acquisition, its negative effect is the tendency to become trapped in an "information cocoon." On the other hand, quantified social recognition (likes, shares, etc.) links popularity with the quality of content, subtly fostering ideological convergencea double-edged sword. While its positive effect is fostering cohesion and efficient cultural dissemination, its negative effect is uneven product quality, market distortions (e.g., short dramas with low-quality content enjoy significant traffic), and a tendency towards product homogeneity. Platforms' overreliance on traffic can suppress people's thinking and pose risks. This article proposes a framework for addressing this issue: increasing the diversity and sensitivity of algorithmic recommendations, enriching content recommendations, and tapping into potential interests. Stakeholders need to improve digital literacy and maintain a balanced regulatory framework, mitigating the risk of content convergence while stimulating its potential utility.
Xinran Ma (Wed,) studied this question.
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