{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,29]],"date-time":"2026-04-29T09:44:21Z","timestamp":1777455861528,"version":"3.51.4"},"reference-count":72,"publisher":"SAGE Publications","issue":"1","license":[{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Big Data &amp; Society"],"published-print":{"date-parts":[[2023,1]]},"abstract":"<jats:p>Using the Internet means encountering algorithmic processes that influence what information a user sees or hears. Existing research has shown that people's algorithm skills vary considerably, that they develop individual theories to explain these processes, and that their online behavior can reflect these understandings. Yet, there is little research on how algorithm skills enable people to use algorithms to their own benefit and to avoid harms they may elicit. To fill this gap in the literature, we explore the extent to which people understand how the online systems and services they use may be influenced by personal data that algorithms know about them, and whether users change their behavior based on this understanding. Analyzing 83 in-depth interviews from five countries about people's experiences with researching and searching for products and services online, we show how being aware of personal data collection helps people understand algorithmic processes. However, this does not necessarily enable users to influence algorithmic output, because currently, options that help users control the level of customization they encounter online are limited. Besides the empirical contributions, we discuss research design implications based on the diversity of the sample and our findings for studying algorithm skills.<\/jats:p>","DOI":"10.1177\/20539517231168100","type":"journal-article","created":{"date-parts":[[2023,4,13]],"date-time":"2023-04-13T00:17:45Z","timestamp":1681345065000},"update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":33,"title":["The importance of algorithm skills for informed Internet use"],"prefix":"10.1177","volume":"10","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0379-710X","authenticated-orcid":false,"given":"Jonathan","family":"Gruber","sequence":"first","affiliation":[{"name":"Department of Communication and Media Research (IKMZ), University of Zurich, Zurich, Switzerland"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4199-4868","authenticated-orcid":false,"given":"Eszter","family":"Hargittai","sequence":"additional","affiliation":[{"name":"Department of Communication and Media Research (IKMZ), University of Zurich, Zurich, Switzerland"}]}],"member":"179","published-online":{"date-parts":[[2023,4,12]]},"reference":[{"key":"bibr1-20539517231168100","unstructured":"Auxier B, Raine L, Anderson M, et al. 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(2016) Data narratives: uncovering tensions in personal data management. In: Proceedings of the 19th ACM conference on computer-supported cooperative work & social computing, New York, NY, USA, 2016, pp.478\u2013490. CSCW \u201816. 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