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John A. Sweeney

dblp:09/8268 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2019
0000-0002-1273-3602ORCID · reported

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

Human-computer interaction and ubiquitous computing · 1

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 · 77% Design research and methods · 23%

Topics — the 1 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Collaborative and social computing › crowdsourcing
large-scale participation
0.412019
WhatFutures: Designing Large-Scale Engagements on WhatsApp · CHI 2019

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

survey · 0.4message analysis · 0.4deployment study · 0.4
YearPublicationVenuePosition
2019 WhatFutures: Designing Large-Scale Engagements on WhatsApp
abstract
WhatsApp, as the world's most popular messaging application, offers significant opportunities for improving the reach and effectiveness of engagement projects. In collaboration with the International Federation of Red Cross and Red Crescent Societies (IFRC) we designed WhatFutures, a collaborative future forecasting engagement for global youth using WhatsApp. WhatFutures was successfully deployed with 487 players across 5 countries (Kenya, Bulgaria, Finland, Australia and Hong Kong) to inform strategic change within the IFRC. Based on our analysis of the activity - including 16,100 messages, 95 multimedia artifacts, and a post-engagement survey - we present a reflection upon the design decisions underpinning WhatFutures and identify how decisions made around group structures, processes and externalization of outputs influenced engagement and data quality. We conclude with the wider implications of our findings for the design of engagements that best utilize the affordances of existing messaging applications.
Daniel Lambton-Howard, Kyle Montague, Andrew Garbett, Shaun Hazeldine, Carlos Alvarez, John A. Sweeney, Patrick Olivier, Ahmed Kharrufa
CHI7