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DTSTART:20201101T020000
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DTSTART:20200308T020000
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UID:12373-59e255e97fc8e0cddcd8732dbd73d230@events.la.psu.edu
DTSTAMP:20260522T004910Z
DTSTART;TZID=America/New_York:20240913T143000
DTEND;TZID=America/New_York:20240913T160000
SUMMARY:“The Lonely Algorithm Problem: Theorizing the Intersection of Algorithmi
	c Personalization and Personal Relationships”
DESCRIPTION:\nA wide variety of social media platforms\, including Insta
	gram\, TikTok\, and Facebook\, claim that their algorithms and A.I. were
	 designed to facilitate social connection and meaningful interpersonal c
	ommunication. But do these claims really match up with the experiences o
	f social media users? Through a series of longitudinal surveys and exper
	iments\, Samuel Taylor will introduce “The Lonely Algorithm Problem” to 
	explain the paradox of algorithmic personalization promoting personal re
	lationships. Drawing from the algorithm responsiveness process framework
	\, this talk will advance a sociotechnical perspective on how algorithms
	 and A.I. influence relationship formation\, maintenance\, and dissoluti
	on processes. Perceived algorithm responsiveness and insensitivity will 
	be positioned as theoretical mechanisms explaining issues central to the
	 lonely algorithm problem. This ongoing research program from Taylor ult
	imately questions claims from social media platforms that tweaks to an a
	lgorithm’s code can cause better personal relationships.\n\n&nbsp\;\n\nS
	amuel Hardman Taylor studies interpersonal and psychological processes i
	n social media\, mobile phones\, and other communication technologies. H
	is research focuses on the implications of digital media for personal re
	lationships and psychological well-being. He is interested in human-comp
	uter interaction\, emphasizing designing new technologies to support rel
	ationships\, empathy\, and mental health. Sam earned his doctoral degree
	 in communication from Cornell University\, and he is currently an assis
	tant professor of communication at the University of Illinois Chicago.\n
	\nFor more details: https://events.la.psu.edu/event/the-lonely-algorithm
	-problem/
X-ALT-DESC;FMTTYPE=text/html:<html><head></head><body><p>A wide variety 
	of social media platforms, including Instagram, TikTok, and Facebook, cl
	aim that their algorithms and A.I. were designed to facilitate social co
	nnection and meaningful interpersonal communication. But do these claims
	 really match up with the experiences of social media users? Through a s
	eries of longitudinal surveys and experiments, Samuel Taylor will introd
	uce “The Lonely Algorithm Problem” to explain the paradox of algorithmic
	 personalization promoting personal relationships. Drawing from the algo
	rithm responsiveness process framework, this talk will advance a sociote
	chnical perspective on how algorithms and A.I. influence relationship fo
	rmation, maintenance, and dissolution processes. Perceived algorithm res
	ponsiveness and insensitivity will be positioned as theoretical mechanis
	ms explaining issues central to the lonely algorithm problem. This ongoi
	ng research program from Taylor ultimately questions claims from social 
	media platforms that tweaks to an algorithm’s code can cause better pers
	onal relationships.</p><p>&nbsp;</p><p>Samuel Hardman Taylor studies int
	erpersonal and psychological processes in social media, mobile phones, a
	nd other communication technologies. His research focuses on the implica
	tions of digital media for personal relationships and psychological well
	-being. He is interested in human-computer interaction, emphasizing desi
	gning new technologies to support relationships, empathy, and mental hea
	lth. Sam earned his doctoral degree in communication from Cornell Univer
	sity, and he is currently an assistant professor of communication at the
	 University of Illinois Chicago.</p><p>For more details: <a href='https:
	//events.la.psu.edu/event/the-lonely-algorithm-problem/'>https://events.
	la.psu.edu/event/the-lonely-algorithm-problem/</a></p></body></html>
LOCATION:158 Willard Building
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