{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,27]],"date-time":"2026-03-27T21:55:48Z","timestamp":1774648548799,"version":"3.50.1"},"reference-count":27,"publisher":"Association for Computing Machinery (ACM)","content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["J. Data and Information Quality"],"abstract":"<jats:p>Disinformation, although an ancient phenomenon, has gained unprecedented reach and speed with the rise of the internet and social media platforms. While traditional fact-checking approaches focus on the semantic content of information, this paper proposes a quantitative analysis based on metadata and formal textual features to investigate disinformation from a quality dimension perspective, assuming that false or misleading information often fails to meet informational quality criteria. Using an experimental approach, we analyzed two datasets of news from reliable and unreliable sources and applied statistical methods, including the Mann-Whitney U test, Cliff\u2019s Delta, and Rosenthal\u2019s r, to measure differences and effect size in the quality dimensions of accuracy, currency, readability, consistency and reliability. The results show that lexical cohesion and lexical diversity are the strongest discriminators of source reliability, followed by structural error rates, while currency and readability display only weak discriminative power. The proposed News Reliability Index (NRI) emerges as a moderate but complementary indicator. Overall, reliable sources consistently demonstrate higher information quality, but structural differences alone are insufficient to detect disinformation, especially considering the capacity of generative AI to produce syntactically coherent texts. We conclude that semantic content analysis remains essential for identifying disinformation, with structural features best applied as supporting signals in detection models. Finally, we highlight future challenges, such as the growing use of artificial intelligence in generating high-quality disinformation, which may reduce the effectiveness of structural metrics and complicate automation in verification processes.<\/jats:p>","DOI":"10.1145\/3802590","type":"journal-article","created":{"date-parts":[[2026,3,27]],"date-time":"2026-03-27T21:13:00Z","timestamp":1774645980000},"update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Measuring the (lack of) quality of disinformation."],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0362-6100","authenticated-orcid":false,"given":"Herbert","family":"Laroca","sequence":"first","affiliation":[{"name":"Universidade de Tr\u00e1s-os-Montes e Alto Douro","place":["Vila Real, Portugal"]},{"name":"Universidade Aberta","place":["Lisbon, Portugal"]}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3314-898X","authenticated-orcid":false,"given":"Vitor","family":"Rocio","sequence":"additional","affiliation":[{"name":"Universidade Aberta","place":["Lisbon, Portugal"]}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3458-7693","authenticated-orcid":false,"given":"Antonio","family":"Cunha","sequence":"additional","affiliation":[{"name":"Universidade de Tras-os-Montes e Alto Douro","place":["Vila Real, Portugal"]},{"name":"Instituto de Engenharia de Sistemas e Computadores, Tecnologia e Ci\u00eancia (INESC TEC)","place":["Porto, Portugal"]}]}],"member":"320","published-online":{"date-parts":[[2026,3,27]]},"reference":[{"key":"e_1_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1057\/9781137388773"},{"key":"e_1_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-07121-3_4"},{"key":"e_1_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-24106-7_2"},{"key":"e_1_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-24106-7_1"},{"key":"e_1_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1002\/(SICI)1097-4571(199106)42:5<351::AID-ASI5>3.0.CO;2-3"},{"key":"e_1_2_1_6_1","volume-title":"Combating fake news in the digital age. Vol.\u00a0 53","author":"Burkhardt M","unstructured":"Joanna\u00a0M Burkhardt. 2017. Combating fake news in the digital age. Vol.\u00a0 53. American Library Association, Chicago, IL, USA."},{"key":"e_1_2_1_7_1","volume-title":"What is disinformation?Library trends 63, 3","author":"Fallis Don","year":"2015","unstructured":"Don Fallis. 2015. What is disinformation?Library trends 63, 3 (2015), 401\u2013426."},{"key":"e_1_2_1_8_1","volume-title":"The philosophy of information","author":"Floridi Luciano","unstructured":"Luciano Floridi. 2013. The philosophy of information. OUP, Oxford."},{"key":"e_1_2_1_9_1","doi-asserted-by":"crossref","first-page":"108432","DOI":"10.1016\/j.cie.2022.108432","article-title":"Linguistic features based framework for automatic fake news detection","volume":"172","author":"Garg Sonal","year":"2022","unstructured":"Sonal Garg and Dilip\u00a0Kumar Sharma. 2022. Linguistic features based framework for automatic fake news detection. Computers & Industrial Engineering 172 (2022), 108432.","journal-title":"Computers & Industrial Engineering"},{"key":"e_1_2_1_10_1","unstructured":"Michael Alexander\u00a0Kirkwood Halliday and Ruqaiya Hasan. 1976. Cohesion in english. Longman."},{"key":"e_1_2_1_11_1","volume-title":"Multidisciplinary International Symposium on Disinformation in Open Online Media. Springer, 29\u201344","author":"Hamers Sandro\u00a0Barres","year":"2023","unstructured":"Sandro\u00a0Barres Hamers and Davide Ceolin. 2023. FaKy: A Feature Extraction Library to Detect the Truthfulness of a Text. In Multidisciplinary International Symposium on Disinformation in Open Online Media. Springer, 29\u201344."},{"key":"e_1_2_1_12_1","volume-title":"Developing Feeds with RSS and Atom: Developers Guide to Syndicating News and Blogs. O\u2019Reilly Media","author":"Hammersley Ben","unstructured":"Ben Hammersley. 2005. Developing Feeds with RSS and Atom: Developers Guide to Syndicating News and Blogs. O\u2019Reilly Media, Inc."},{"key":"e_1_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-07121-3_14"},{"key":"e_1_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-07121-3_2"},{"key":"e_1_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11042-023-15792-1"},{"key":"e_1_2_1_16_1","volume-title":"Do You Speak Disinformation? Computational Detection of Deceptive News-Like Content Using Linguistic and Stylistic Features. Digital Journalism","author":"Lebernegg No\u00eblle","year":"2024","unstructured":"No\u00eblle Lebernegg, Jakob-Moritz Eberl, Petro Tolochko, and Hajo Boomgaarden. 2024. Do You Speak Disinformation? Computational Detection of Deceptive News-Like Content Using Linguistic and Stylistic Features. Digital Journalism (2024), 1\u201324."},{"key":"e_1_2_1_17_1","volume-title":"Linguistic approaches to fake news detection. Data science for fake news: Surveys and perspectives","author":"Lugea Jane","year":"2021","unstructured":"Jane Lugea. 2021. Linguistic approaches to fake news detection. Data science for fake news: Surveys and perspectives (2021), 287\u2013302."},{"key":"e_1_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.5555\/2655323"},{"key":"e_1_2_1_19_1","volume-title":"2020 IEEE Asia-Pacific conference on computer science and data engineering (CSDE). IEEE, 1\u20136.","author":"Ngada Okuhle","year":"2020","unstructured":"Okuhle Ngada and Bertram Haskins. 2020. Fake news detection using content-based features and machine learning. In 2020 IEEE Asia-Pacific conference on computer science and data engineering (CSDE). IEEE, 1\u20136."},{"key":"e_1_2_1_20_1","volume-title":"Proceedings of the 27th International Conference on Computational Linguistics. 3391\u20133401","author":"P\u00e9rez-Rosas Ver\u00f3nica","year":"2018","unstructured":"Ver\u00f3nica P\u00e9rez-Rosas, Bennett Kleinberg, Alexandra Lefevre, and Rada Mihalcea. 2018. Automatic Detection of Fake News. In Proceedings of the 27th International Conference on Computational Linguistics. 3391\u20133401."},{"key":"e_1_2_1_21_1","volume-title":"Proceedings of the twelfth language resources and evaluation conference. 1404\u20131413","author":"Santos Roney","year":"2020","unstructured":"Roney Santos, Gabriela Pedro, Sidney Leal, Oto Vale, Thiago Pardo, Kalina Bontcheva, and Carolina Scarton. 2020. Measuring the impact of readability features in fake news detection. In Proceedings of the twelfth language resources and evaluation conference. 1404\u20131413."},{"key":"e_1_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.1145\/3137597.3137600"},{"key":"e_1_2_1_23_1","doi-asserted-by":"publisher","DOI":"10.1177\/07395329241242819"},{"key":"e_1_2_1_24_1","volume-title":"CEUR Workshop Proceedings, Vol.\u00a0 3370","author":"Tavakoli Mohammadali","year":"2023","unstructured":"Mohammadali Tavakoli, Harith Alani, and Gr\u00e9goire Burel. 2023. On the Readability of Misinformation in Comparison to the Truth. In CEUR Workshop Proceedings, Vol.\u00a0 3370. 63\u201372."},{"key":"e_1_2_1_25_1","unstructured":"Dave Winer. 2003. RSS 2.0 Specification. http:\/\/blogs. law. harvard. edu\/tech\/rss(2003)."},{"key":"e_1_2_1_26_1","volume-title":"Proceedings of the Annual Meeting of the Cognitive Science Society, Vol.\u00a0 43","author":"Withall Amanda","year":"2021","unstructured":"Amanda Withall and Eyal Sagi. 2021. The impact of readability on trust in information. In Proceedings of the Annual Meeting of the Cognitive Science Society, Vol.\u00a0 43."},{"key":"e_1_2_1_27_1","doi-asserted-by":"crossref","first-page":"102739","DOI":"10.1016\/j.ipm.2021.102739","article-title":"Users\u2019 ability to perceive misinformation: An information quality assessment approach","volume":"59","author":"Zrnec Alja\u017e","year":"2022","unstructured":"Alja\u017e Zrnec, Marko Po\u017eenel, and Dejan Lavbi\u010d. 2022. Users\u2019 ability to perceive misinformation: An information quality assessment approach. Information Processing & Management 59, 1 (2022), 102739.","journal-title":"Information Processing & Management"}],"container-title":["Journal of Data and Information Quality"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3802590","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,3,27]],"date-time":"2026-03-27T21:13:13Z","timestamp":1774645993000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3802590"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,3,27]]},"references-count":27,"alternative-id":["10.1145\/3802590"],"URL":"https:\/\/doi.org\/10.1145\/3802590","relation":{},"ISSN":["1936-1955","1936-1963"],"issn-type":[{"value":"1936-1955","type":"print"},{"value":"1936-1963","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,3,27]]},"assertion":[{"value":"2025-06-25","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2026-02-04","order":2,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2026-03-27","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}],"article-number":"3802590"}}