Determining Causes and Severity of End-User Frustration
By Irina Ceaparu, J. Lazar, Katie Bessière, John P. Robinson, Ben Shneiderman. International journal of human computer interactions, 2004
400 citations recorded by the source corpus.
Subfields: Gender Studies, Information Systems and Management, Sociology and Political Science
View Paper: https://www.semanticscholar.org/paper/7eff871ce258420be2cdcaadf2f2aecf5df4330a
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Information Systems and Management
In Sociology and Political Science
- Cristian Danescu-Niculescu-Mizil
- Justin Cheng
- Michael S. Bernstein
- Jure Leskovec
- Ion Stoica
- Manuel Gomez-Rodriguez
- Jaewon Yang
Citations in the corpus
- Understanding the impact of video quality on user engagement (2011, background): “This knowledge can help providers to better invest their network and server resources toward optimizing the quality metrics that really matter [3].”
- An Integrative Theory of Motivation, Volition, and Performance (2008, background): “Ceaparu et al (2004) conducted a series of self-report and observational measures at two universities to determine causes and severity of user frustration when using computers.”
- Anyone Can Become a Troll: Causes of Trolling Behavior in Online Discussions (2017, background): “, poor interface design or slow loading times [12]) may further temper aggression.”
- Panappticon: Event-based tracing to measure mobile application and platform performance (2013, background): “…Lide Zhang* David R. Bild Robert P. Dick Z. Morley Mao Peter Dinda* * Facebook Inc. EECS Department, * EECS Department, Menlo Park, CA, USA University of Michigan Northwestern University lidezhang@fb.com Ann Arbor, MI, USA Evanston, IL, USA {drbild,zmao,dickrp}@umich.edu…”
- Catch me if you can: performance bug detection in the wild (2011, background): “As research in human-computer interaction has shown, the key determinant of perceptible performance is the system’s lag in handling user events [5, 6, 24, 25].”
- What Frustrates Screen Reader Users on the Web: A Study of 100 Blind Users (2007, methodology): “Theuseoftimediariestotrackuserfrustra-tionshasproventobethemosteffectivemethodofgaininginformation(Ceaparuet al.,2004).”