{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,2]],"date-time":"2026-05-02T06:54:18Z","timestamp":1777704858311,"version":"3.51.4"},"reference-count":11,"publisher":"SAGE Publications","issue":"2","license":[{"start":{"date-parts":[[2020,6,6]],"date-time":"2020-06-06T00:00:00Z","timestamp":1591401600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Journal of Intelligent &amp; Fuzzy Systems"],"published-print":{"date-parts":[[2020,8,31]]},"abstract":"<jats:p>In the context of digital social media, where users have multiple ways to obtain information, it is important to have tools to detect the authorship within a corpus supposedly created by a single author. With the tremendous amount of information coming from social networks there is a lot of research concerning author profiling, but there is a lack of research about the authorship identification. In order to detect the author of a group of tweets, a Na\u00efve Bayes classifier is proposed which is an automatic algorithm based on Bayes\u2019 theorem. The main objective is to determine if a particular tweet was made by a specific user or not, based on its content. The data used correspond to a simple data set, obtained with the Twitter API, composed of four political accounts accompanied by their username and tweet identifier as it is mixed with multiple user tweets. To describe the performance of the classification model and interpret the obtained results, a confusion matrix is used as it contains values like accuracy, sensitivity, specificity, Kappa measure, the positive predictive and negative predictive value. These results show that the prediction model, after several cases of use, have acceptable values against the observed probabilities.<\/jats:p>","DOI":"10.3233\/jifs-179894","type":"journal-article","created":{"date-parts":[[2020,6,9]],"date-time":"2020-06-09T12:55:55Z","timestamp":1591707355000},"page":"2331-2339","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":3,"title":["Author detection: Analyzing tweets by using a Na\u00efve Bayes classifier"],"prefix":"10.1177","volume":"39","author":[{"given":"Roc\u00edo","family":"Abascal-Mena","sequence":"first","affiliation":[{"name":"Department of Information Technologies, Universidad Aut\u00f3noma Metropolitana, Unidad Cuajimalpa. Avenida Vasco de Quiroga 4871, Colonia. Santa Fe, Cuajimalpa. Delegaci\u00f3n Cuajimalpa de Morelos. C.P. 05348, Ciudad de M\u00e9xico, M\u00e9xico"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Erick","family":"L\u00f3pez-Ornelas","sequence":"additional","affiliation":[{"name":"Department of Information Technologies, Universidad Aut\u00f3noma Metropolitana, Unidad Cuajimalpa. Avenida Vasco de Quiroga 4871, Colonia. Santa Fe, Cuajimalpa. Delegaci\u00f3n Cuajimalpa de Morelos. C.P. 05348, Ciudad de M\u00e9xico, M\u00e9xico"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"179","published-online":{"date-parts":[[2020,6,6]]},"reference":[{"key":"e_1_3_1_2_2","unstructured":"CastroA. and LindauerB. Author Identification on Twitter 2012."},{"key":"e_1_3_1_3_2","doi-asserted-by":"crossref","unstructured":"SriramB. Short text classification in twitter to improve information filtering. Doctoral dissertation The Ohio State University. 2010.","DOI":"10.1145\/1835449.1835643"},{"key":"e_1_3_1_4_2","unstructured":"MurthyD. Twitter: Social Communication in the Twitter Age. Cambridge UK: Polity Press (2013) pp. 193."},{"issue":"7","key":"e_1_3_1_5_2","first-page":"319","article-title":"Investigating the use of machine learning algorithms in detecting gender of the Arabic tweet author","volume":"1","author":"AlSukhni E.","year":"2016","unstructured":"AlSukhniE. and AlequrQ., Investigating the use of machine learning algorithms in detecting gender of the Arabic tweet author, International Journal of Advanced Computer Science & Applications1(7) (2016), 319\u2013328.","journal-title":"International Journal of Advanced Computer Science & Applications"},{"key":"e_1_3_1_6_2","unstructured":"BurgerJ.D. HendersonJ. KimG. and ZarrellaG. Discriminating Gender on Twitter. Proceedings of the Conference on Empirical Methods in Natural Language Processing. EMNLP \u201911 Association for Computational Linguistics Stroudsburg PA USA. 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Authorship recognition of tweets: A comparison between social behavior and linguistic profiles IEEE International Conference on Systems Man and Cybernetics (SMC) (2017) 471\u2013476.","DOI":"10.1109\/SMC.2017.8122650"},{"issue":"1","key":"e_1_3_1_8_2","first-page":"42","article-title":"Supervised machine learning for the detection of troll profiles in twitter social network: Application to a real case of cyberbullying","volume":"24","author":"Gal\u00e1n-Garc\u00eda P.","year":"2016","unstructured":"Gal\u00e1n-Garc\u00edaP., PuertaJ.G.D.L., G\u00f3mezC.L., SantosI. and BringasP.G., Supervised machine learning for the detection of troll profiles in twitter social network: Application to a real case of cyberbullying, Logic Journal of the IGPL24(1) (2016), 42\u201353.","journal-title":"Logic Journal of the IGPL"},{"key":"e_1_3_1_9_2","unstructured":"GreenR. and SheppardJ. Comparting frequency- and style-based features for twitter author identification Proceedings of the International Florida Artificial Intelligence Research Society Conference (FLAIRS) 2013."},{"key":"e_1_3_1_10_2","doi-asserted-by":"crossref","unstructured":"Sousa SilvaR. LaboreiroG. SarmentoL. GrantT. OliveiraE. and MaiaB. \u2018twazn me!!!;(\u2018 Automatic authorship analysis of micro-blogging messages. Mu\u00f1oz R. Montoyo A. M\u00e9tais E. (eds) Natural Language Processing and Information Systems NLDB 2011. Lecture Notes in Computer Science vol 6716. Springer Berlin Hidelberg. (2011) pp. 161\u2013168.","DOI":"10.1007\/978-3-642-22327-3_16"},{"key":"e_1_3_1_11_2","unstructured":"MechtiS. JaouaM. BelguithL.H. and FaizR. Machine learning for classifying authors of anonymous tweets blogs reviews and social media. Proceedings of the PAN@ CLEF Sheffield England. 2014."},{"key":"e_1_3_1_12_2","doi-asserted-by":"crossref","unstructured":"PhanX.H. NguyenL.M. and HoriguchiS. 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