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Experiment 1 demonstrates the utility of process-related knowledge in user evaluations of agency: individuals with little knowledge of AJ prefer attributions of human authorship over news stories attributed to algorithms, whereas individuals with high AJ knowledge have an equal or stronger preference for news that is described as algorithmically generated. Experiment 2 conditions these effects to show how prior characterizations of AJ\u2014whether more machine- or human-like\u2014shape evaluations of algorithmically generated news contingent on user age and knowledge level. Effects are found for differing age groups at lower levels of AJ knowledge, where\n                    <jats:italic toggle=\"yes\">machine-like<\/jats:italic>\n                    characterizations enhance evaluations of algorithmically generated news for younger users but ascribing\n                    <jats:italic toggle=\"yes\">human-like<\/jats:italic>\n                    traits enhances evaluations of automated news for older users.\n                  <\/jats:p>","DOI":"10.1177\/14614448221142534","type":"journal-article","created":{"date-parts":[[2022,12,23]],"date-time":"2022-12-23T06:35:26Z","timestamp":1671777326000},"page":"5898-5922","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":21,"title":["Knowledge of automated journalism moderates evaluations of algorithmically generated news"],"prefix":"10.1177","volume":"26","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1237-6163","authenticated-orcid":false,"given":"Wonseok (Eric)","family":"Jang","sequence":"first","affiliation":[{"name":"Sungkyunkwan University, South Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dae Hee","family":"Kwak","sequence":"additional","affiliation":[{"name":"University of Michigan, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4925-2244","authenticated-orcid":false,"given":"Erik","family":"Bucy","sequence":"additional","affiliation":[{"name":"Texas Tech University, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"179","published-online":{"date-parts":[[2022,12,23]]},"reference":[{"key":"e_1_3_4_2_1","doi-asserted-by":"publisher","DOI":"10.1080\/08838151.2019.1653101"},{"key":"e_1_3_4_3_1","doi-asserted-by":"publisher","DOI":"10.1177\/1077699015606057"},{"key":"e_1_3_4_4_1","doi-asserted-by":"publisher","DOI":"10.1080\/21670811.2014.976412"},{"key":"e_1_3_4_5_1","doi-asserted-by":"crossref","unstructured":"Diakopoulos N (2014) Algorithmic Accountability Reporting: On the Investigation of Black Boxes. 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