id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
cord-356353-e6jb0sex	Fourcade, Marion	Loops, ladders and links: the recursivity of social and machine learning	2020-08-26		.txt	text/plain	14364	644	42	Both practices rely upon and reinforce a pervasive appetite for digital input or feedback that we characterize as "data hunger." They also share a propensity to assemble insight and make meaning accretively-a propensity that we denote here as "world or meaning accretion." Throughout this article, we probe the dynamic interaction of social and machine learning by drawing examples from one genre of online social contention and connection in which the pervasive influence of machine learning is evident: namely, that which occurs across social media channels and platforms. In such settings, the data accretion upon which machine learning depends for the development of granular insights-and, on social media platforms, associated auctioning and targeting of advertising-compounds the cumulative, sedimentary effect of social data, making negative impressions generated by "revenge porn," or by one's online identity having been fraudulently coopted, hard to displace or renew.	./cache/cord-356353-e6jb0sex.txt	./txt/cord-356353-e6jb0sex.txt