{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,22]],"date-time":"2025-10-22T03:09:18Z","timestamp":1761102558096,"version":"build-2065373602"},"reference-count":77,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2024,12,5]],"date-time":"2024-12-05T00:00:00Z","timestamp":1733356800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Computers"],"abstract":"<jats:p>Background: Artificial intelligence poses a critical challenge to the authenticity of journalistic documents. Objectives: This research proposes a method to automatically identify AI-generated news articles based on various stylistic features. Methods\/Approach: We used machine learning algorithms and trained five classifiers to distinguish journalistic news articles from their AI-generated counterparts based on various lexical, syntactic, and readability features. BERTopic was used to extract salient keywords from these articles, which were then used to prompt Google\u2019s Gemini to generate new artificial articles on the same topic. Results: The Random Forest classifier performed the best on the task (accuracy = 98.3%, precision = 0.984, recall = 0.983, and F1-score = 0.983). Random Forest feature importance, Analysis of Variance (ANOVA), Mutual Information, and Recursive Feature Elimination revealed the top five important features: sentence length range, paragraph length coefficient of variation, verb ratio, sentence complex tags, and paragraph length range. Conclusions: This research introduces an innovative approach to prompt engineering using the BERTopic modelling technique and identifies key stylistic features to distinguish AI-generated content from human-generated content. Therefore, it contributes to the ongoing efforts to combat disinformation, enhancing the credibility of content in various industries, such as academic research, education, and journalism.<\/jats:p>","DOI":"10.3390\/computers13120328","type":"journal-article","created":{"date-parts":[[2024,12,5]],"date-time":"2024-12-05T04:13:03Z","timestamp":1733371983000},"page":"328","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Distinguishing Human Journalists from Artificial Storytellers Through Stylistic Fingerprints"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0009-0003-9356-0321","authenticated-orcid":false,"given":"Van Hieu","family":"Tran","sequence":"first","affiliation":[{"name":"Faculty of Science and Technology, Charles Darwin University, Casuarina, NT 0810, Australia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0499-6565","authenticated-orcid":false,"given":"Yakub","family":"Sebastian","sequence":"additional","affiliation":[{"name":"Faculty of Science and Technology, Charles Darwin University, Casuarina, NT 0810, Australia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8532-6816","authenticated-orcid":false,"given":"Asif","family":"Karim","sequence":"additional","affiliation":[{"name":"Faculty of Science and Technology, Charles Darwin University, Casuarina, NT 0810, Australia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7572-9750","authenticated-orcid":false,"given":"Sami","family":"Azam","sequence":"additional","affiliation":[{"name":"Faculty of Science and Technology, Charles Darwin University, Casuarina, NT 0810, Australia"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2024,12,5]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"615","DOI":"10.5114\/biolsport.2023.125623","article-title":"From human writing to artificial intelligence generated text: Examining the prospects and potential threats of ChatGPT in academic writing","volume":"40","author":"Dergaa","year":"2023","journal-title":"Biol. Sport"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"313","DOI":"10.1126\/science.adg7879","article-title":"CHATGPT is fun, but not an author","volume":"379","author":"Thorp","year":"2023","journal-title":"Science"},{"key":"ref_3","unstructured":"Moran, C. (2023, August 02). ChatGPT Is Making up Fake Guardian Articles. Here\u2019s How We\u2019re Responding. The Guardian, 2023. Available online: https:\/\/www.theguardian.com\/commentisfree\/2023\/apr\/06\/ai-chatgpt-guardian-technology-risks-fake-article."},{"key":"ref_4","unstructured":"Robitzski, D. (2023, August 03). New AI Generates Horrifyingly Plausible Fake News. Futurism, 2019. Available online: https:\/\/futurism.com\/ai-generates-fake-news."},{"key":"ref_5","unstructured":"Thompson, S.A. (2023, August 02). AI-Generated Content Discovered on News Sites, Content Farms and Product Reviews. The New York Times, 2023. Available online: https:\/\/www.nytimes.com\/2023\/05\/19\/technology\/ai-generated-content-discovered-on-news-sites-content-farms-and-product-reviews.html."},{"key":"ref_6","unstructured":"Hurst, L. (2023, August 10). Ai-generated Fake News Websites Driving Spread of Misinformation. Euronews, 2023. Available online: https:\/\/www.euronews.com\/next\/2023\/05\/02\/rapid-growth-of-news-sites-using-ai-tools-like-chatgpt-is-driving-the-spread-of-misinforma."},{"key":"ref_7","unstructured":"Fitch, A. (2023, August 02). Readers Beware: AI Has Learned to Create Fake News Stories. The Wall Street Journal, 2019. Available online: https:\/\/www.wsj.com\/articles\/readers-beware-ai-has-learned-to-create-fake-news-stories-11571018640."},{"key":"ref_8","unstructured":"Armstrong, M., and Richter, F. (2023, August 02). Infographic: Fake News Is a Real Problem. Statista Daily Data, 2016. Available online: https:\/\/www.statista.com\/chart\/6795\/fake-news-is-a-real-problem\/."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"280","DOI":"10.1016\/j.bjps.2023.09.033","article-title":"Fact or fake news: What are Ai Chatbots telling our patients about aesthetic surgery?","volume":"86","author":"Citron","year":"2023","journal-title":"J. Plast. Reconstr. Aesthetic Surg."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"226","DOI":"10.1016\/j.mcpdig.2023.05.004","article-title":"Learning to fake it: Limited responses and fabricated references provided by ChatGPT for medical questions","volume":"1","author":"Gravel","year":"2023","journal-title":"Mayo Clin. Proc. Digit. Health"},{"key":"ref_11","unstructured":"Li, X., Zhang, Y., and Malthouse, E.C. (2023). A preliminary study of CHATGPT on news recommendation: Personalization, provider fairness, fake news. arXiv."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"2120","DOI":"10.1007\/s10439-023-03248-4","article-title":"In reference to \u2018role of chat GPT in public health\u2019, to highlight the AI\u2019s incorrect reference generation","volume":"51","author":"Frosolini","year":"2023","journal-title":"Ann. Biomed. Eng."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"589","DOI":"10.14778\/2732286.2732295","article-title":"Toward Computational Fact-checking","volume":"7","author":"Wu","year":"2014","journal-title":"Proc. VLDB Endow."},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Ciampaglia, G.L., Shiralkar, P., Rocha, L.M., Bollen, J., Menczer, F., and Flammini, A. (2015). Computational Fact Checking from Knowledge Networks. PLoS ONE, 10.","DOI":"10.1371\/journal.pone.0141938"},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Shi, B., and Weninger, T. (2016, January 11\u201315). Fact Checking in Heterogeneous Information Networks. Proceedings of the 25th International Conference Companion on World Wide Web\u2014WWW\u201916 Companion, Montreal, QC, Canada.","DOI":"10.1145\/2872518.2889354"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"68","DOI":"10.1145\/1409360.1409378","article-title":"Open information extraction from the web","volume":"51","author":"Etzioni","year":"2008","journal-title":"Commun. ACM"},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Magdy, A., and Wanas, N. (2010, January 30). Web-based statistical fact checking of textual documents. Proceedings of the 2nd International Workshop on Search and Mining User-Generated Contents, Toronto, ON, Canada.","DOI":"10.1145\/1871985.1872002"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"355","DOI":"10.1561\/1500000046","article-title":"Credibility in Information Retrieval","volume":"9","author":"Ginsca","year":"2015","journal-title":"Found. Trends Inf. Retr."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"194","DOI":"10.1016\/j.geb.2010.01.005","article-title":"Spread of (mis)information in social networks","volume":"70","author":"Acemoglu","year":"2010","journal-title":"Games Econ. Behav."},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Budak, C., Agrawal, D., and El Abbadi, A. (2011, January 28). Limiting the spread of misinformation in social networks. Proceedings of the 20th International Conference on World Wide Web\u2014WWW\u201911, Hyderabad, India.","DOI":"10.1145\/1963405.1963499"},{"key":"ref_21","unstructured":"Nguyen, N.P., Yan, G., Thai, M.T., and Eidenbenz, S. (2012, January 22\u201324). Containment of misinformation spread in online social networks. Proceedings of the 3rd Annual ACM Web Science Conference on\u2014WebSci\u201912, Evanston, IL, USA."},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Kwon, S., Cha, M., Jung, K., Chen, W., and Wang, Y. (2013, January 7\u201310). Prominent Features of Rumor Propagation in Online Social Media. Proceedings of the 2013 IEEE 13th International Conference on Data Mining, Dallas, TX, USA.","DOI":"10.1109\/ICDM.2013.61"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"1198","DOI":"10.1016\/j.chb.2015.01.024","article-title":"Collective attention in the age of (mis)information","volume":"51","author":"Mocanu","year":"2015","journal-title":"Comput. Hum. Behav."},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Tambuscio, M., Ruffo, G., Flammini, A., and Menczer, F. (2015, January 18\u201322). Fact-checking Effect on Viral Hoaxes. Proceedings of the 24th International Conference on World Wide Web\u2014WWW \u201915 Companion, Florence, Italy.","DOI":"10.1145\/2740908.2742572"},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Wei, Z., Chen, J., Gao, W., Li, B., Zhou, L., He, Y., and Wong, K.F. (2017). An Empirical Study on Uncertainty Identification in Social Media Context. World Sci. Ebooks, 79\u201388.","DOI":"10.1142\/9789813223615_0007"},{"key":"ref_26","first-page":"1","article-title":"News in an online world: The need for an \u2018automatic crap detector\u2019","volume":"52","author":"Chen","year":"2015","journal-title":"Proc. Assoc. Inf. Sci. Technol."},{"key":"ref_27","unstructured":"Rubin, V., Conroy, N., and Chen, Y. (2023, November 12). Towards News Verification: Deception Detection Methods for News Discourse Towards News Verification: Deception Detection Methods for News Discourse. Available online: https:\/\/sites.socsci.uci.edu\/~lpearl\/colareadinggroup\/readings\/RubinEtAl2015_DeceptionDetectionNews.pdf."},{"key":"ref_28","unstructured":"Badaskar, S., Agarwal, S., and Arora, S. (2008, January 7\u201312). Identifying Real or Fake Articles: Towards better Language Modeling. Proceedings of the Third International Joint Conference on Natural Language Processing, Hyderabad, India."},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Afroz, S., Brennan, M., and Greenstadt, R. (2012, January 20\u201323). Detecting Hoaxes, Frauds, and Deception in Writing Style Online. Proceedings of the 2012 IEEE Symposium on Security and Privacy, San Francisco, CA, USA. Available online: https:\/\/ieeexplore.ieee.org\/document\/6234430.","DOI":"10.1109\/SP.2012.34"},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Rubin, V., Conroy, N., Chen, Y., and Cornwell, S. (2016, January 17). Fake News or Truth? Using Satirical Cues to Detect Potentially Misleading News. Proceedings of the Second Workshop on Computational Approaches to Deception Detection, San Dieg, CA, USA.","DOI":"10.18653\/v1\/W16-0802"},{"key":"ref_31","unstructured":"Potthast, M., Kiesel, J., Reinartz, K., Bevendorff, J., and Stein, B. (August, January 30). A Stylometric Inquiry into Hyperpartisan and Fake News. Proceedings of the Association for Computational Linguistics, Vancouver, BC, Canada."},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Popat, K., Mukherjee, S., Str\u00f6tgen, J., and Weikum, G. (2016, January 24\u201328). Credibility assessment of textual claims on the web. Proceedings of the 25th ACM International Conference on Information and Knowledge Management, Indianapolis, IN, USA.","DOI":"10.1145\/2983323.2983661"},{"key":"ref_33","unstructured":"Perez-Rosas, V., Kleinberg, B., Lefevre, A., and Mihalcea, R. (2018, January 20\u201326). Automatic detection of fake news. Proceedings of the 27th International Conference on Computational Linguistics, Santa Fe, NM, USA."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"377","DOI":"10.1016\/j.procs.2020.01.035","article-title":"Analysis of classifiers for fake news detection","volume":"165","author":"Agarwal","year":"2019","journal-title":"Procedia Comput. Sci."},{"key":"ref_35","unstructured":"Kumarage, T., Garland, J., Bhattacharjee, A., Trapeznikov, K., Ruston, S., and Liu, H. (2023). Stylometric Detection of AI-Generated Text in Twitter Timelines. arXiv."},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Herbold, S., Hautli-Janisz, A., Heuer, U., Kikteva, Z., and Trautsch, A. (2023). A large-scale comparison of human-written versus ChatGPT-generated essays. Sci. Rep., 13.","DOI":"10.1038\/s41598-023-45644-9"},{"key":"ref_37","unstructured":"Ma, Y., Liu, J., Yi, F., Cheng, Q., Huang, Y., Lu, W., and Liu, X. (2024). AI vs. Human-Differentiation Analysis of Scientific Content Generation. arXiv."},{"key":"ref_38","unstructured":"Google (2024, January 05). Introducing Gemini: Our Largest and Most Capable AI Model. Google. Available online: https:\/\/blog.google\/technology\/ai\/google-gemini-ai\/#performance."},{"key":"ref_39","unstructured":"Yana, G.Y. (2024, June 01). Does Gemini Generate Humanized Writing? Read or Die!. Available online: https:\/\/medium.com\/read-or-die\/does-gemini-generate-humanized-writing-746ce5e78d1c."},{"key":"ref_40","unstructured":"Thomas, L. (2024, January 11). Friedman Official Biography. Available online: https:\/\/www.thomaslfriedman.com\/official-bio\/."},{"key":"ref_41","unstructured":"(2024, January 14). 2022 Gordon Award Winner Konrad Marshall. Melbourne Press Club. Available online: https:\/\/www.melbournepressclub.com\/article\/2022-gordon-award-winner-konrad-marshall."},{"key":"ref_42","unstructured":"(2024, January 16). Dave Philipps. The New York Times. Available online: https:\/\/www.nytimes.com\/by\/dave-philipps."},{"key":"ref_43","unstructured":"Nicholas, D. (2024, January 19). Kristof of The New York Times. The Pulitzer Prizes. Available online: https:\/\/www.pulitzer.org\/winners\/nicholas-d-kristof."},{"key":"ref_44","unstructured":"(2024, January 20). David Swan|Linkedin. (n.d). Available online: https:\/\/au.linkedin.com\/in\/davidswanoz."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"93","DOI":"10.1080\/19312458.2018.1430754","article-title":"Applying LDA topic modeling in communication research: Toward a valid and reliable methodology","volume":"12","author":"Maier","year":"2018","journal-title":"Commun. Methods Meas."},{"key":"ref_46","doi-asserted-by":"crossref","unstructured":"Egger, R., and Yu, J. (2022). A topic modeling comparison between LDA, NMF, Top2Vec; Bertopic to demystify twitter posts. Front. Sociol., 7.","DOI":"10.3389\/fsoc.2022.886498"},{"key":"ref_47","first-page":"207","article-title":"Investigating variations in adjective use across different text categories","volume":"41","author":"Cao","year":"2009","journal-title":"Adv. Comput. Linguist. J. Res. Comput. Sci."},{"key":"ref_48","unstructured":"Distante, E. (2023, December 20). BERTopic: Topic Modeling As You Have Never Seen It Before. Medium, 2022. Available online: https:\/\/medium.com\/data-reply-it-datatech\/bertopic-topic-modeling-as-you-have-never-seen-it-before-abb48bbab2b2."},{"key":"ref_49","unstructured":"(2023, December 20). BERTopic, Spacy Universe (No Date) BERTopic. Available online: https:\/\/spacy.io\/universe\/project\/bertopic."},{"key":"ref_50","unstructured":"(2023, December 01). Natural Language Toolkit. NLTK. Available online: https:\/\/www.nltk.org\/."},{"key":"ref_51","unstructured":"(2023, December 01). NLTK tokenize package. NLTK. Available online: https:\/\/www.nltk.org\/api\/nltk.tokenize.html."},{"key":"ref_52","unstructured":"Albanese, N.C. (2023, December 10). Topic Modeling with LSA, PLSA, LDA, NMF, Bertopic, top2vec: A Comparison. Medium, 2022. Available online: https:\/\/towardsdatascience.com\/topic-modeling-with-lsa-plsa-lda-nmf-bertopic-top2vec-a-comparison-5e6ce4b1e4a5#5763."},{"key":"ref_53","unstructured":"(2023, December 10). Deepanshi. Text Preprocessing in NLP with Python Codes. Analytics Vidhya. Available online: https:\/\/www.analyticsvidhya.com\/blog\/2021\/06\/text-preprocessing-in-nlp-with-python-codes\/."},{"key":"ref_54","unstructured":"Nugues, P.M. (2006). Words, parts of speech; morphology. Springer eBooks, Springer."},{"key":"ref_55","unstructured":"Lex, E., Granitzer, M., Muhr, M., and Juffinger, A. (2010). Stylometric features for emotion level classification in news related blogs. Adapt. Pers. Fusion Heterog. Inf., 132\u2013133."},{"key":"ref_56","unstructured":"Rittman, R., and Wacholder, N. (2008, January 1\u20134). Adjectives and adverbs as indicators of affective language for automatic genre detection. Proceedings of the AISB 2008 Convention Communication, Interaction and Social Intelligence, Aberdeen, UK."},{"key":"ref_57","unstructured":"Sokolova, M., and Lapalme, G. (2023, December 10). Verbs as the Most Affective Words. Available online: http:\/\/rali.iro.umontreal.ca\/rali\/sites\/default\/files\/publis\/VerbsAffect2.pdf."},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"217","DOI":"10.1023\/B:JOPR.0000027963.80639.88","article-title":"Nouns and Verbs: A comparison of Definitional style","volume":"33","author":"Marinellie","year":"2004","journal-title":"J. Psycholinguist. Res."},{"key":"ref_59","doi-asserted-by":"crossref","unstructured":"Polinsky, M., and Magyar, L. (2020). Headedness and the Lexicon: The Case of Verb-to-Noun Ratios. Languages, 5.","DOI":"10.3390\/languages5010009"},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"554","DOI":"10.1016\/j.system.2012.10.012","article-title":"Effects of text length on lexical diversity measures: Using short texts with less than 200 tokens","volume":"40","author":"Koizumi","year":"2012","journal-title":"System"},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"99","DOI":"10.1515\/csh-2023-0002","article-title":"Parts-of-Speech (PoS) Analysis and Classification of Various Text Genres","volume":"1","author":"Mendhakar","year":"2023","journal-title":"Corpus-based Stud. Across Humanit."},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"349","DOI":"10.1002\/meet.1450410141","article-title":"Adjectives as indicators of subjectivity in documents","volume":"41","author":"Rittman","year":"2004","journal-title":"Proc. Am. Soc. Inf. Sci. Technol."},{"key":"ref_63","doi-asserted-by":"crossref","unstructured":"Weiss, Z., Riemenschneider, A., Schr\u00f6ter, P., and Meurers, D. (2019, January 2). Computationally Modeling the Impact of Task-Appropriate Language Complexity and Accuracy on Human Grading of German Essays. Proceedings of the Fourteenth Workshop on Innovative Use of NLP for Building Educational Applications, Florence, Italy.","DOI":"10.18653\/v1\/W19-4404"},{"key":"ref_64","doi-asserted-by":"crossref","unstructured":"Karlgren, J., and Cutting, D. (1994, January 5\u20139). Recognizing text genres with simple metrics using discriminant analysis. Proceedings of the 15th Conference on Computational Linguistics, Kyoto, Japan.","DOI":"10.3115\/991250.991324"},{"key":"ref_65","first-page":"155","article-title":"Tertiary education of journalists and the readability of Australian newspapers","volume":"26","author":"McLellan","year":"2004","journal-title":"Aust. Journal. Rev."},{"key":"ref_66","doi-asserted-by":"crossref","first-page":"1093","DOI":"10.1007\/s12553-021-00574-2","article-title":"An objective analysis of quality and readability of online information on COVID-19","volume":"11","author":"Kelly","year":"2021","journal-title":"Health Technol."},{"key":"ref_67","unstructured":"Scott, B. (2023, December 25). The Coleman-Liau Readability Formula. ReadabilityFormulas.com. 27 September 2023. Available online: https:\/\/readabilityformulas.com\/the-coleman-liau-readability-formula\/."},{"key":"ref_68","doi-asserted-by":"crossref","unstructured":"Rohith, H.P., Sooda, K., Rai, K.B., and Srinivas, D.B. (2023, January 23\u201325). A natural language processing system for truth detection and text summarization. Proceedings of the 2023 7th International Conference on Computing Methodologies and Communication (ICCMC), Erode, India.","DOI":"10.1109\/ICCMC56507.2023.10083948"},{"key":"ref_69","doi-asserted-by":"crossref","unstructured":"Shabani, V., Havolli, A., Maraj, A., and Fetahu, L. (2023, January 6\u201310). Fake news detection using naive Bayes classifier and passive aggressive classifier. Proceedings of the 2023 12th Mediterranean Conference on Embedded Computing (MECO), Budva, Montenegro.","DOI":"10.1109\/MECO58584.2023.10155036"},{"key":"ref_70","doi-asserted-by":"crossref","first-page":"7763","DOI":"10.1007\/s00500-022-06773-x","article-title":"Machine learning for fake news classification with optimal feature selection","volume":"26","author":"Fayaz","year":"2022","journal-title":"Soft Comput."},{"key":"ref_71","unstructured":"Alshaher, H. (2021). Studying the Effects of Feature Scaling in Machine Learning. [Ph.D. Dissertation, North Carolina Agricultural and Technical State University]."},{"key":"ref_72","doi-asserted-by":"crossref","first-page":"70","DOI":"10.1016\/j.neucom.2017.11.077","article-title":"Feature selection in machine learning: A new perspective","volume":"300","author":"Cai","year":"2018","journal-title":"Neurocomputing"},{"key":"ref_73","doi-asserted-by":"crossref","first-page":"1","DOI":"10.5121\/ijdkp.2015.5201","article-title":"A review on Evaluation Metrics for Data Classification Evaluations","volume":"5","author":"Hossin","year":"2015","journal-title":"Int. J. Data Min. Knowl. Manag. Process"},{"key":"ref_74","unstructured":"(2024, February 12). Cross-Validation: Evaluating Estimator Performance\u2014Scikit-Learn 0.21.3 Documentation. Scikit-Learn.org. Available online: https:\/\/scikit-learn.org\/stable\/modules\/cross_validation.html."},{"key":"ref_75","doi-asserted-by":"crossref","first-page":"448","DOI":"10.1177\/01655515211007710","article-title":"Binary background model with geometric mean for author-independent authorship verification","volume":"49","author":"Canbay","year":"2021","journal-title":"J. Inf. Sci."},{"key":"ref_76","doi-asserted-by":"crossref","first-page":"19522","DOI":"10.1007\/s10489-023-04453-3","article-title":"Contrastive learning with text augmentation for text classification","volume":"53","author":"Jia","year":"2023","journal-title":"Appl. Intell."},{"key":"ref_77","first-page":"1008","article-title":"Is Automated Journalistic Writing Less Biased? An Experimental Test of Auto-Written and Human-Written News Stories","volume":"14","author":"Wu","year":"2019","journal-title":"Journal. Pract."}],"container-title":["Computers"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2073-431X\/13\/12\/328\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T16:47:29Z","timestamp":1760114849000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2073-431X\/13\/12\/328"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,12,5]]},"references-count":77,"journal-issue":{"issue":"12","published-online":{"date-parts":[[2024,12]]}},"alternative-id":["computers13120328"],"URL":"https:\/\/doi.org\/10.3390\/computers13120328","relation":{},"ISSN":["2073-431X"],"issn-type":[{"type":"electronic","value":"2073-431X"}],"subject":[],"published":{"date-parts":[[2024,12,5]]}}}