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Jonathan Scott Morgan

dblp:126/1836 · DBLP profile ↗
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1ranked-venue papers
1as first author
0since 2021 · last 2013
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Human-computer interaction and ubiquitous computing · 1 · 1 first-author

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Human-computer interaction and pervasive computing
1 paper
Collaborative and social computing · 100%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Collaborative and social computing › social media › media sharing
news sharing
0.212013
Is news sharing on Twitter ideologically biased? · CSCW 2013
Collaborative and social computing
selective exposure
0.212013
Is news sharing on Twitter ideologically biased? · CSCW 2013
Collaborative and social computing
social media
0.212013
Is news sharing on Twitter ideologically biased? · CSCW 2013

Methods — techniques the papers use, named apart from their topics

quantitative analysis · 0.2
YearPublicationVenuePosition
2013 Is news sharing on Twitter ideologically biased?
abstract
In this paper we explore effects of perceived ideology of news outlets on consumption and sharing of news in Twitter. Selective exposure theory suggests that when given access to a broad range of information, people will tend to consume and share news that confirms their existing beliefs and biases. We find that users share news in similar ways regardless of outlet or perceived ideology of outlet, and that as a user shares more news content, they tend to quickly include outlets with opposing viewpoints. This suggests that while perceived ideology does not inspire most Twitter users to treat liberal or conservative news outlets differently, it is a factor in their news consumption and sharing. Specifically, users in our sample who sent multiple tweets tended to increase the ideological diversity in news they shared within two or three tweets, and users' information diversity increased as their number of tweets sent increased.
Jonathan Scott Morgan, Cliff Lampe, Zubair Shafiq
CSCW1