J
Jason Wiese
Researcher at University of Utah
Publications - 52
Citations - 2123
Jason Wiese is an academic researcher from University of Utah. The author has contributed to research in topics: Computer science & Context (language use). The author has an hindex of 15, co-authored 42 publications receiving 1900 citations. Previous affiliations of Jason Wiese include Microsoft & Carnegie Mellon University.
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I’m the Mayor of My House: Examining Why People Use Foursquare - A Social-Driven Location Sharing Application
TL;DR: The results of three studies focusing on the foursquare check-in system are presented, both qualitatively and quantitatively, to understand how and why people use location sharing applications, as well as how they manage their privacy.
Proceedings ArticleDOI
I'm the mayor of my house: examining why people use foursquare - a social-driven location sharing application
TL;DR: The authors conducted interviews and two surveys to understand how and why people use location sharing applications, as well as how they manage their privacy, and discuss implications for design of mobile social services.
Proceedings ArticleDOI
Toss 'n' turn: smartphone as sleep and sleep quality detector
TL;DR: The rapid adoption of smartphones along with a growing habit for using these devices as alarm clocks presents an opportunity to use this device as a sleep detector, and individual models performed better than generally trained models on detecting sleep and sleep quality.
Proceedings ArticleDOI
The post that wasn't: exploring self-censorship on facebook
Manya Sleeper,Rebecca Balebako,Sauvik Das,Amber Lynn McConahy,Jason Wiese,Lorrie Faith Cranor +5 more
TL;DR: The results from an 18-participant user study designed to explore self-censorship behavior as well as the subset of unshared content participants would have potentially shared if they could have specifically targeted desired audiences are reported.
Proceedings ArticleDOI
Are you close with me? are you nearby?: investigating social groups, closeness, and willingness to share
TL;DR: The findings show that self-reported closeness is the strongest indicator of willingness to share, and individuals are more likely to share in scenarios with common information than other kinds of scenarios, and frequency of communication predicts both closeness and willingness to sharing better than frequency of collocation.