The Crowd Computing research group investigates distributed forms of work, where the tasks are too challenging for computers alone. Given the recent advances in AI, it is now imperative to identify and harness the unique aspects of human cognition and develop ways for humans and algorithms to collaborate seamlessly across different domains.
Activities
Digital Health; We employ mobile sensing through wearable computing and smartphones to build interactive and crowd-powered digital health solutions. Some of our core foci here include improved wellbeing in terms of sleep and mental health, and investigating mHealth solutions for chronic pain.
Crowdsourcing; We investigate novel crowdsourcing and human computation processes as well as the fundamental human characteristics that affect digital labour: motivation, data quality, and social aspects of work.
Applied Interactive Systems; We build and study solutions that harness the crowds across different application domains. Examples of such systems include crowd-powered decision support through modelling large-scale subjective data or creativity support through on-demand access to crowd cognition.
Selected Publications
2024
Alorwu A, van Berkel N, Visuri A, Suryanarayana SA, Yoshihiro T & Hosio S (2024)
Monetary Valuation of Personal Health Data in the Wild
International Journal of Human-Computer Studies (IJHCS) – https://doi.org/10.1016/j.ijhcs.2024.103241
Mourelatos E, Simonen J, Hosio S, Likhobaba D, Ustalov D (2024)
How has the COVID-19 pandemic shaped behavior in crowdsourcing? The role of online labor market training
Journal of Business Economics (JBE) – https://doi.org/10.1007/s11573-024-01196-6
Wester J, Pohl H, Hosio S & Van Berkel N (2024)
“This Chatbot Would Never…”: Perceived Moral Agency of Mental Health Chatbots
Proceedings of the ACM on Human-Computer Interaction (CSCW) – https://doi.org/10.1145/3637410
Kuutila M, Kiili C, Kupiainen R, Huusko E, Li J, Hosio S, Mäntylä M, Coiro J, Kiili K (2024)
Revealing complexities when adult readers engage in the credibility evaluation of social media posts
Computers in Human Behaviour (CHB) – https://doi.org/10.1016/j.chb.2023.108017
2023
Kuosmanen E, Huusko E, Van Berkel N, Nunes F, Vega J, Goncalves J, Khamis M, Esteves A, Ferreira D & Hosio S (2023)
Exploring Crowdsourced Self-Care Techniques: A Study on Parkinson’s Disease
International Journal of Human-Computer Studies (IJHCS) – https://doi.org/10.1016/j.ijhcs.2023.103062
Kheirinejad S, Visuri A, Suryanarayana S & Hosio S (2023)
Exploring mHealth Applications for Self-Management of Chronic Low Back Pain: A Survey of Features and Benefits
Heliyon – https://doi.org/10.1016/j.heliyon.2023.e16586
Paananen V, Kiarostami S, Lee LH, Braudt T, Hosio S (2023)
From Digital Media to Empathic Spaces: A Systematic Review of Empathy Research in Extended Reality Environments
ACM Computing Surveys (CSUR) – https://doi.org/10.1145/3626518
Kheirinejad S, Visuri A, Ferreira D & Hosio S (2022)
“Leave Your Smartphone Out of Bed”: Quantitative Analysis of Smartphone Use on Sleep Quality
In Personal and Ubiquitous Computing – https://doi.org/10.1007/s00779-022-01694-w
2022
Kuosmanen E, Visuri A, Kheirinejad S, van Berkel N, Koskimäki H, Ferreira D & Hosio S (2022)
How Does Sleep Tracking Influence Your Life? Experiences from a Longitudinal Field Study with a Wearable Ring*
In Proceedings of the ACM International Conference on Mobile Human-Computer Interaction (Mobile HCI ’22) – https://doi.org/10.1145/3546720
* Best Paper Honourable Mention Award
Asare KO, Moshe I, Terhorst Y, Vega J, Hosio S, Baumaister H, Pulkki-Råback L & Ferreira D (2022)
Mood ratings and digital biomarkers from smartphone and wearable data differentiates and predicts depression status: A longitudinal data analysis
Pervasive and Mobile Computing – https://doi.org/10.1016/j.pmcj.2022.101621
Alorwu A, Visuri A, van Berkel N & Hosio S (2022)
(Re)using Crowdsourced Health Data: Perceptions of Data Contributors
IEEE Software – https://doi.org/10.1109/MS.2021.3117684
2021
Alorwu A, Kheirinejad S, Van berkel N, Kinnula M, Ferreira D, Visuri A & Hosio S (2021)
Assessing MyData Scenarios: Ethics, Concerns, and the Promise
In Proceedings of the ACM SIGCHI Conference on Human Factors in Computing Systems 2021 (CHI’21) – https://doi.org/10.1145/3411764.3445213
Visuri A, Van Berkel N, Goncalves J, Rawassizadeh R, Ferreira D, Kostakos V (2021)
Understanding usage style transformation during long-term smartwatch use
Personal and Ubiquitous Computing – https://doi.org/10.1007/s00779-020-01511-2
People
Simo Hosio
Associate Professor
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Scholar
Aku Visuri
Academy Postdoctoral Researcher
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Scholar
Mahmoud Badri
Doctoral researcher (part-time)
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LinkedIn
Saba Kheirinejad
Doctoral researcher
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Scholar
Dániel Szabó
Doctoral Researcher
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LinkedIn | GitHub
Mohammadreza Sadeghi
Research Assistant
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Alumni:
- Dr. Ville Paananen
- Mähä Eldamnhory
- Kavindu Magalage
- Achira Hendalage
- Niloofar Meftahi
- Katri Säily
- Dr. Denzil Ferreira
- Dr. Kennedy Opoku Asare
- Dr. Andy Alorwu
- Dr. Sharadhi Suryanarayana
- Joonas Moilanen
- Danial Khaledi
- Piushana Abeygunawardena
- Maha Eldamnhory
- Eetu Huusko
- Sina Kiarostami
- Dr. Elina Kuosmanen
- Dr. Jonas Oppenlaender
Funded Projects
SleepVention: Academy Research Fellow (Aku Visuri, 2023-2027) + research costs: A Data-driven recommender platform for improving sleep and wellbeing through digital tracking and interventions
AIM: Academy Research Fellow (Simo Hosio, 2022-2027) + research costs: Crowdsourcing Clinically Relevant, Non-Biased Datasets for Medical Artificial Intelligence
Academy of Finland & JSPS Bilateral Mobility Funding between University of Oulu (Finland) and University of Tokyo (Japan): Culturally Adaptive Conversational Agents for Mental Health Self-Care in Higher Education
CRITICAL: An Academy of Finland (Strategic Research Council) project on Technological and Societal Innovations to Cultivate Critical Reading in the Internet Era
GenZ: Generation Z and beyond: Co-evolution of human capabilities and intelligent technologies in the 21st century (GenZ)
ICON: Interventions and Contextual Understanding for Low Back Pain Research