Elections in the twenty-first century are not only fought in parliaments, or television studios; they unfold across digital platforms shaped by invisible algorithms. Every scroll, click, and swipe is guided by ranking and recommendation systems that determine what information citizens see, what advertisements reach them, and how political messages spread. While some portray algorithms as all-powerful tools capable of swinging entire elections, a closer look suggests a more complicated picture. Algorithms are better understood as amplifiers: they structure visibility, accelerate certain narratives, and suppress others, but their effects depend heavily on context, user behaviour, and broader social dynamics.This paper critically reviews the role of algorithms in shaping electoral outcomes, drawing on research from computer science, political communication, and political economy. It examines three main pathways: (1) how algorithms filter and rank information, (2) how they enable personalization and political microtargeting, and (3) how they facilitate or hinder the spread of misinformation. In addition, the paper introduces three theoretical perspectives—computational propaganda, media ecology, and the political economy of communication—to frame how algorithms interact with politics at structural, cultural, and systemic levels.The evidence shows that algorithms do matter, and their effects are uneven. Most studies suggest modest average impacts on individual opinions, though targeted campaigns and sustained exposure may have larger, cumulative consequences. Blind spots remain: short-term experiments cannot capture long-term influence, researchers rarely have access to raw platform data, and vulnerable subgroups remain underexplored.The conclusion argues that algorithms do not decide elections alone, but they have become inseparable
N. N. Puri (Thu,) studied this question.