{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,16]],"date-time":"2026-06-16T05:31:29Z","timestamp":1781587889503,"version":"3.54.5"},"reference-count":86,"publisher":"SAGE Publications","issue":"1","license":[{"start":{"date-parts":[[2022,2,24]],"date-time":"2022-02-24T00:00:00Z","timestamp":1645660800000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"funder":[{"name":"The Swedish Foundation for Humanities and Social Science"}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Hum Factors"],"published-print":{"date-parts":[[2024,1]]},"abstract":"<jats:sec>\n                    <jats:title>Objective<\/jats:title>\n                    <jats:p>We examine individuals\u2019 ability to detect social bots among Twitter personas, along with participant and persona features associated with that ability.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Social media users need to distinguish bots from human users. We develop and demonstrate a methodology for assessing those abilities, with a simulated social media task.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Method<\/jats:title>\n                    <jats:p>We analyze performance from a signal detection theory perspective, using a task that asked lay participants whether each of 50 Twitter personas was a human or social bot. We used the agreement of two machine learning models to estimate the probability of each persona being a bot. We estimated the probability of participants indicating that a persona was a bot with a generalized linear mixed-effects model using participant characteristics (social media experience, analytical reasoning, and political views) and stimulus characteristics (bot indicator score and political tone) as regressors.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>On average, participants had modest sensitivity (d\u2019) and a criterion that favored responding \u201chuman.\u201d Exploratory analyses found greater sensitivity for participants (a) with less self-reported social media experience, (b) greater analytical reasoning ability, and (c) who were evaluating personas with opposing political views. Some patterns varied with participants' political identity.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>Individuals have limited ability to detect social bots, with greater aversion to mistaking bots for humans than vice versa. Greater social media experience and myside bias appeared to reduce performance, as did less analytical reasoning ability.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Application<\/jats:title>\n                    <jats:p>These patterns suggest the need for interventions, especially when users feel most familiar with social media.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1177\/00187208211072642","type":"journal-article","created":{"date-parts":[[2022,2,24]],"date-time":"2022-02-24T17:20:33Z","timestamp":1645723233000},"page":"88-102","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":20,"title":["Duped by Bots: Why Some are Better than Others at Detecting Fake Social Media Personas"],"prefix":"10.1177","volume":"66","author":[{"given":"Ryan","family":"Kenny","sequence":"first","affiliation":[{"name":"Carnegie Mellon University, Pittsburgh, PA, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Baruch","family":"Fischhoff","sequence":"additional","affiliation":[{"name":"Carnegie Mellon University, Pittsburgh, PA, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Alex","family":"Davis","sequence":"additional","affiliation":[{"name":"Carnegie Mellon University, Pittsburgh, PA, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kathleen M.","family":"Carley","sequence":"additional","affiliation":[{"name":"Carnegie Mellon University, Pittsburgh, PA, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5325-3798","authenticated-orcid":false,"given":"Casey","family":"Canfield","sequence":"additional","affiliation":[{"name":"Missouri University of Science and Technology, Rolla, MI, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"179","published-online":{"date-parts":[[2022,2,24]]},"reference":[{"key":"bibr1-00187208211072642","doi-asserted-by":"crossref","unstructured":"Aiello L. M., Deplano M., Schifanella R., Ruffo G. (2012). People are strange when you're a stranger: Impact and influence of bots on social networks. In Proceedings of the International AAAI Conference on Web and Social Media, Dublin, Ireland, 4\u20138 June 2012, (Vol. 6, No. 1).","DOI":"10.1609\/icwsm.v6i1.14236"},{"key":"bibr2-00187208211072642","doi-asserted-by":"publisher","DOI":"10.1002\/acp.975"},{"key":"bibr3-00187208211072642","doi-asserted-by":"publisher","DOI":"10.1007\/s11747-019-00695-1"},{"key":"bibr4-00187208211072642","doi-asserted-by":"publisher","DOI":"10.1126\/science.aaa1160"},{"key":"bibr5-00187208211072642","doi-asserted-by":"publisher","DOI":"10.1177\/0956797615594620"},{"key":"bibr6-00187208211072642","doi-asserted-by":"publisher","DOI":"10.1017\/S1930297500004927"},{"key":"bibr7-00187208211072642","volume-title":"Finding and characterizing information warfare campaigns","author":"Beskow D.","year":"2020"},{"key":"bibr95-00187208211072642","unstructured":"Beskow D., Carley K. (2018a). Bot-hunter: A tiered approach to detecting & characterizing automated activity on twitter. In Conference: SBP-BRiMS: International Conference on Social Computing, Behavioral-Cultural Modeling and Prediction and Behavior Representation in Modeling and Simulation, Washington, DC, 10-13th July 2018."},{"key":"bibr9-00187208211072642","volume-title":"International conference on social computing, behavioral-cultural modeling and prediction and behavior representation in modeling and simulation","author":"Beskow D.","year":"2018"},{"key":"bibr11-00187208211072642","doi-asserted-by":"publisher","DOI":"10.1080\/00140138108924833"},{"key":"bibr12-00187208211072642","doi-asserted-by":"publisher","DOI":"10.1007\/s10979-007-9110-z"},{"key":"bibr13-00187208211072642","unstructured":"Botometer (2021). 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A categorisation of social media bot accounts","author":"Stieglitz S.","year":"2017"},{"key":"bibr77-00187208211072642","volume-title":"Social media bots draw public\u2019s attention and concern","volume":"15","author":"Stocking G.","year":"2018"},{"key":"bibr78-00187208211072642","doi-asserted-by":"publisher","DOI":"10.1215\/03616878-1460524"},{"key":"bibr79-00187208211072642","doi-asserted-by":"publisher","DOI":"10.1007\/s11109-007-9050-9"},{"key":"bibr80-00187208211072642","author":"Timberg C.","year":"2018","journal-title":"Washington Post"},{"key":"bibr81-00187208211072642","doi-asserted-by":"publisher","DOI":"10.1002\/acp.915"},{"key":"bibr82-00187208211072642","doi-asserted-by":"publisher","DOI":"10.3758\/s13421-011-0104-1"},{"key":"bibr83-00187208211072642","volume-title":"Elections integrity data archive","author":"Twitter","year":"2019"},{"key":"bibr84-00187208211072642","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-61255-9_2"},{"issue":"2","key":"bibr85-00187208211072642","first-page":"1","author":"Uyheng J.","year":"2020","journal-title":"Journal of Computational Social Science"},{"key":"bibr86-00187208211072642","doi-asserted-by":"publisher","DOI":"10.1007\/s41109-021-00362-x"},{"key":"bibr87-00187208211072642","doi-asserted-by":"publisher","DOI":"10.1609\/icwsm.v11i1.14871"},{"key":"bibr88-00187208211072642","doi-asserted-by":"publisher","DOI":"10.7551\/mitpress\/10859.001.0001"},{"key":"bibr89-00187208211072642","doi-asserted-by":"publisher","DOI":"10.1109\/IRI.2013.6642447"},{"key":"bibr90-00187208211072642","doi-asserted-by":"publisher","DOI":"10.1518\/hfes.45.1.104.27233"},{"key":"bibr91-00187208211072642","doi-asserted-by":"publisher","DOI":"10.1080\/03637751.2016.1272761"},{"key":"bibr93-00187208211072642","doi-asserted-by":"publisher","DOI":"10.1080\/09658211.2012.654799"},{"key":"bibr94-00187208211072642","doi-asserted-by":"publisher","DOI":"10.1145\/3373464.3373475"}],"container-title":["Human Factors: The Journal of the Human Factors and Ergonomics Society"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.1177\/00187208211072642","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.sagepub.com\/doi\/full-xml\/10.1177\/00187208211072642","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.1177\/00187208211072642","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,4,29]],"date-time":"2026-04-29T07:53:09Z","timestamp":1777449189000},"score":1,"resource":{"primary":{"URL":"https:\/\/journals.sagepub.com\/doi\/10.1177\/00187208211072642"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,2,24]]},"references-count":86,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2024,1]]}},"alternative-id":["10.1177\/00187208211072642"],"URL":"https:\/\/doi.org\/10.1177\/00187208211072642","relation":{},"ISSN":["0018-7208","1547-8181"],"issn-type":[{"value":"0018-7208","type":"print"},{"value":"1547-8181","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,2,24]]}}}