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YouTube has a pattern of recommending right-leaning and Christian videos, even to users who haven’t previously interacted with that kind of content, according to a recent study of the platform ...
Algorithmic radicalization is the concept that recommender algorithms on popular social media sites such as YouTube and Facebook drive users toward progressively more extreme content over time, leading to them developing radicalized extremist political views. Algorithms record user interactions, from likes/dislikes to amount of time spent on ...
Basically, these methods use an item profile (i.e., a set of discrete attributes and features) characterizing the item within the system. To abstract the features of the items in the system, an item presentation algorithm is applied. A widely used algorithm is the tf–idf representation (also called vector space representation). [57]
The paper on the algorithm was first published by Beate Commentz-Walter in 1979 through the Saarland University and typed by "R. Scherner". [1] The paper detailed two differing algorithms she claimed combined the idea of the Aho-Corasick and Boyer-Moore algorithms, which she called algorithms B and B1. The paper mostly focuses on algorithm B ...
The alt-right pipeline (also called the alt-right rabbit hole) is a proposed conceptual model regarding internet radicalization toward the alt-right movement. It describes a phenomenon in which consuming provocative right-wing political content, such as antifeminist or anti-SJW ideas, gradually increases exposure to the alt-right or similar far-right politics.
This list of most-liked YouTube videos contains the top 30 videos with the most likes of all time, taken directly from the video page. The American video platform YouTube implemented a like and dislike button on these pages in March 2010, part of a major redesign of the site.
Connected-component labeling (CCL), connected-component analysis (CCA), blob extraction, region labeling, blob discovery, or region extraction is an algorithmic application of graph theory, where subsets of connected components are uniquely labeled based on a given heuristic.
In computer science, Thompson's construction algorithm, also called the McNaughton–Yamada–Thompson algorithm, [1] is a method of transforming a regular expression into an equivalent nondeterministic finite automaton (NFA). [2] This NFA can be used to match strings against the regular expression. This algorithm is credited to Ken Thompson.