Filter bubbles

This is an important subject for us. As this is a test article, I’m just going to include a sample text right now, this one is a definition of Filter bubbles, from Wikipedia.

A filter bubble – a term coined by Internet activist Eli Pariser – is a state of intellectual isolation[1] that can result from personalized searches when a website algorithm selectively guesses what information a user would like to see based on information about the user, such as location, past click-behavior and search history.[2][3][4] As a result, users become separated from information that disagrees with their viewpoints, effectively isolating them in their own cultural or ideological bubbles.[5] The choices made by these algorithms are not transparent. Prime examples include Google Personalized Search results and Facebook‘s personalized news-stream. The bubble effect may have negative implications for civic discourse, according to Pariser, but contrasting views regard the effect as minimal[6] and addressable.[7] The surprising results of the U.S. presidential election in 2016 have been associated with the influence of social media platforms such as Twitter and Facebook,[8][9] and as a result have called into question the effects of the “filter bubble” phenomenon on user exposure to fake news and echo chambers,[10] spurring new interest in the term,[11] with many concerned that the phenomenon may harm democracy.[12][13][11]
(Technologies such as social media) lets you go off with like-minded people, so you’re not mixing and sharing and understanding other points of view … It’s super important. It’s turned out to be more of a problem than I, or many others, would have expected.
— Bill Gates 2017 in Quartz[14]

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