Internet platforms increase ideological polarization and group separation compared to pre-internet times
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Studies consistently find that modern social media and algorithmic platforms contribute to ideological polarization, echo chambers, and affective division. However, the retrieved literature does not provide a direct historical comparison to pre-internet times.
Social media platforms are one of the most important domains in which artificial intelligence (AI) has already transformed the nature of economic and social interaction. AI enables the massive scale and highly personalized nature of online information sharing that we now take for granted. Extensive attention has been devoted to the polarization that social media platforms appear to facilitate. However, a key implication of the transformation we are experiencing due to these AI-powered platforms has received much less attention: how platforms impact what observers of online discourse come to believe about community views. These observers include policymakers and legislators, who look to social media to gauge the prospects for policy and legislative change, as well as developers of AI models trained on large-scale internet data, whose outputs may similarly reflect a distorted view of public opinion. In this paper, we present a nested game-theoretic model to show how observed online opinion is produced by the interaction of the decisions made by users about whether and with what rhetorical intensity to share their opinions on a platform, the efforts of viewpoint organizations (such as traditional media and advocacy organizations) that seek to encourage or discourage opinion-sharing online, and the operation of AI-powered recommender systems controlled by social media platforms. We show that signals from ideological viewpoint organizations encourage an increase in rhetorical inte
Much like television and radio, the introduction of the internet, and subsequently social media, has fundamentally changed the way presidential candidates' campaign in the United States. The evolution of the internet has created a heightened level of scrutiny for candidates but has also provided a resource that grants unprecedented access and reach to potential voters. Campaigns have become more dependent on the use of social media marketing not only because of this reach but also because of the affordability. The internet has proven to be an ever-growing business that has inspired radical changes in presidential campaign strategies. The results of this study reveal that social media plays a dual role in U.S. presidential elections. Social media platforms such as Facebook and Instagram significantly increase voter turnout, particularly among younger demographics, while also reinforcing partisan identities and intensifying ideological stances. However, these benefits are accompanied by challenges, including the spread of misinformation, the creation of echo chambers, and ethical concerns surrounding micro-targeted political advertisements. These findings underscore the transformative impact of social media on political behavior, highlighting both its potential to enhance democratic participation and its risks of deepening polarization. The conclusions advocate for increased digital literacy, regulatory measures, and ethical campaigning to ensure that social media serves as a c
This study investigates how algorithm-driven short-form video platforms (e.g., TikTok, Instagram Reels) shape political perceptions and contribute to affective political polarization among Pakistani youth. A quantitative cross-sectional survey was conducted with a sample of 390 young adults (aged 18–30) in Lahore, Pakistan, selected using convenience sampling. Data were collected via a structured questionnaire measuring platform usage, exposure to algorithmically curated political content, and affective polarization. Descriptive statistics, chi-square tests of independence, and binary logistic regression were employed for analysis. Results indicate that 64.1% of respondents spend over three hours daily on short-form video platforms. A majority (57.2%) agreed that algorithms repeatedly show similar political viewpoints, leading to the perception of ideological echo chambers (46.9% rarely see opposing views). Logistic regression revealed that daily consumption of political short-form videos significantly predicts affective political polarization (B = 1.43, p < .001), with heavy users being over four times more likely to report heightened emotional attachment to political groups. The study confirms the existence of a "digital trap" where algorithmic personalization reinforces existing beliefs, limits exposure to diverse perspectives, and intensifies affective polarization. These findings have critical implications for media literacy interventions, platform governance, and democr
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