Yes­ter­day I linked an arti­cle about the “Dark For­est The­o­ry of the Inter­net”. Today I stum­bled upon this sci­en­tif­ic paper regard­ing the seg­re­ga­tion of parts of the social Inter­net into “echo cham­bers”.

While social media make it easy to con­nect with and access infor­ma­tion from any­one, they also facil­i­tate basic influ­ence and unfriend­ing mech­a­nisms that may lead to seg­re­gat­ed and polar­ized clus­ters known as “echo cham­bers.”

Exam­ple of a polar­ized and seg­re­gat­ed net­work on Twit­ter.

Here we study the con­di­tions in which such echo cham­bers emerge by intro­duc­ing a sim­ple mod­el of infor­ma­tion shar­ing in online social net­works with the two ingre­di­ents of influ­ence and unfriend­ing. Users can change both opin­ions and social con­nec­tions based on the infor­ma­tion to which they are exposed through shar­ing. Mod­el dynam­ics demon­strate that even with min­i­mal amounts of influ­ence and unfriend­ing, the social net­work rapid­ly devolves into seg­re­gat­ed, homo­ge­neous com­mu­ni­ties. These pre­dic­tions are con­sis­tent with empir­i­cal data from Twit­ter. Although our find­ings sug­gest that echo cham­bers are some­what inevitable giv­en the mech­a­nisms at play in online social media, they also pro­vide insights into pos­si­ble mit­i­ga­tion strate­gies.

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