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On shapes and sizes: Measuring diversity of technological engagement through digital visitors and residents maps
Author(s) -
Harvey William,
Hood Erin M.,
Connaway Lynn Silipigni
Publication year - 2017
Publication title -
proceedings of the association for information science and technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.193
H-Index - 14
ISSN - 2373-9231
DOI - 10.1002/pra2.2017.14505401018
Subject(s) - metric (unit) , context (archaeology) , computer science , world wide web , diversity (politics) , data science , meaning (existential) , software , information retrieval , psychology , sociology , geography , engineering , anthropology , operations management , archaeology , psychotherapist , programming language
The Digital Visitors and Residents (V&R) project developed a mapping exercise to help individuals better understand their engagement with technology and the web. The map creation process and the opportunity for individuals to share their stories in a group setting can be fun, informative and educational. In this paper, we show that collections of V&R maps can be sources of rich and interesting information about similarities and differences in individuals' engagement with technology. Computational methods such as shape analysis and machine learning can be used to distill this information from collections of V&R maps. We present several models, techniques and algorithms for V&R map analysis that may be familiar to many data scientists and software developers, including a shape metric that captures properties of shapes with intuitive meaning and interpretation in the V&R context. Patterns and trends emerging from collections of maps can help a team better understand their similarities and differences in engagement with technology or help inform decisions on the design of information technology or library technology services. We provide examples of these techniques using data collected in various V&R mapping sessions. Finally, we introduce a V&R mapping web application designed for touchscreens that can ease data collection for computational analysis and provide a fun and engaging experience for mapping exercise participants.