@inproceedings{huang2022covid,
author = {Huang, Yue and Obada-Obieh, Borke and Redmiles, Elissa M. and Lokam, Satya and Beznosov, Konstantin},
title = {COVID-19 Information-Tracking Solutions: A Qualitative Investigation of the Factors Influencing People’s Adoption Intention},
year = {2022},
isbn = {9781450391863},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url_Official_Copy = {https://doi.org/10.1145/3498366.3505756},
doi = {10.1145/3498366.3505756},
abstract = {Numerous information-tracking solutions have been implemented worldwide to fight the COVID-19 pandemic. While prior work has heavily explored the factors affecting people’s willingness to adopt contact-tracing solutions, which inform people when they have been exposed to someone positive for COVID-19, numerous countries have implemented other information-tracking solutions that use more data and more sensitive data than these commonly studied contact-tracing apps. In this work, we build on existing work focused on contact-tracing apps to explore adoption and design considerations for six representative information-tracking solutions for COVID-19, which differ in their goals and in the types of information they collect. To do so, we conducted semi-structured interviews with 44 participants to investigate the factors that influence their willingness to adopt these solutions. We find four main categories of influences on participants’ willingness to adopt such solutions: individual benefits of the solution, societal benefits of the solution, functionality concern, and digital safety (e.g., security and privacy) concerns. Further, we enumerate the factors that inform participants’ evaluations of these categories. Based on our findings, we make recommendations for the future design of information-tracking solutions and discuss how different factors may balance against benefits in future crisis situations.},
booktitle = {Proceedings of the 2022 Conference on Human Information Interaction and Retrieval},
pages = {12–24},
numpages = {13},
keywords = {information sharing, data practices, Usable privacy and security},
location = {Regensburg, Germany},
series = {CHIIR '22}
}

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M.","Lokam, S.","Beznosov, K."],"bibdata":{"bibtype":"inproceedings","type":"inproceedings","author":[{"propositions":[],"lastnames":["Huang"],"firstnames":["Yue"],"suffixes":[]},{"propositions":[],"lastnames":["Obada-Obieh"],"firstnames":["Borke"],"suffixes":[]},{"propositions":[],"lastnames":["Redmiles"],"firstnames":["Elissa","M."],"suffixes":[]},{"propositions":[],"lastnames":["Lokam"],"firstnames":["Satya"],"suffixes":[]},{"propositions":[],"lastnames":["Beznosov"],"firstnames":["Konstantin"],"suffixes":[]}],"title":"COVID-19 Information-Tracking Solutions: A Qualitative Investigation of the Factors Influencing People’s Adoption Intention","year":"2022","isbn":"9781450391863","publisher":"Association for Computing Machinery","address":"New York, NY, USA","url_official_copy":"https://doi.org/10.1145/3498366.3505756","doi":"10.1145/3498366.3505756","abstract":"Numerous information-tracking solutions have been implemented worldwide to fight the COVID-19 pandemic. 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