Curation and privacy in mobile application UI repositories

Mobile interaction mining allows everyday interaction data to be mined for insights into the best performing design patterns, usability problems, and overall design trends. So far, this data has primarily come from automated application exploration or crowdworkers completing smartphone tasks as part of a study. Both of these methods have a primary issue that the interaction patterns do not quite align with how everyday users interact with applications. However, mining interaction traces that contain personally identifiable information from real users presents a problem, mainly when that data is to be published. This thesis provides an exploratory look at the data curation and privacy considerations required to share mobile application interaction data publicly. Regarding the privacy side, we will focus on applications in the Finance and Health categories.

Name thesis:degree_name

M.S.

Level thesis:degree_level

Thesis

Discipline thesis:degree_discipline

Computer Science

Grantor

University of Illinois at Urbana-Champaign

Year dc:date

2019

Author dc:creator

• Melvin, Oliver

Contributors dc:contributor

• Kumar, Ranjitha

• Interaction Mining
• Mobile UX
• Mobile Privacy
• HCI

Statement dc:rights

• Copyright 2019 Oliver Melvin

Language dc:language

en

Handle dc:identifier

http://hdl.handle.net/2142/105842

OAI identifier oai:identifier

oai:www.ideals.illinois.edu:2142/105842