eprintid: 19477 rev_number: 2 eprint_status: archive userid: 1 dir: disk0/00/01/94/77 datestamp: 2024-06-04 14:11:57 lastmod: 2024-06-04 14:11:57 status_changed: 2024-06-04 14:05:48 type: article metadata_visibility: show creators_name: AbuSalim, S.W.G. creators_name: Mostafa, S.A. creators_name: Mustapha, A. creators_name: Ibrahim, R. creators_name: Wahab, M.H.A. title: Identifying Cyberspace Usersâ�� Tendency in Blog Writing Using Machine Learning Algorithms ispublished: pub note: cited By 1; Conference of 3rd International Conference on Engineering Mathematics and Computing, ICEMC 2020 ; Conference Date: 5 February 2020 Through 7 February 2020; Conference Code:284739 abstract: A blog is a form of direct interactive communication technology, which allows users to interact and communicate with each other through posting comments and sharing links as well. A blog is a platform where a writer or group of writers gives their opinion on a specific topic. Many issues and topics that are in a certain country being censored and controlled by the government from being presented through the mass media. Nevertheless, blogs have the space to provide a wide platform for exchanging ideas and opinions on various issues. There is a specific proportion between blog features and bloggersâ�� tendency to social, political, and cultural patterns of different countries and nations that create trends among the bloggers in these countries. In this paper, we use an existing data set from previous research, which has 100 records of data, and manipulate the data by applying three machine learning algorithms for implementing classification and regression tasks. The algorithms are Decision Tree (c4.5), Linear Regression (LR), and Decision Forest (DF) with a 10-fold cross-validation method for training and testing. The results showed that C4.5 achieves the best overall results of 81 accuracy, 83 precision, and 91 recall, compared with the other two algorithms. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. date: 2023 official_url: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85140780716&doi=10.1007%2f978-981-19-2300-5_6&partnerID=40&md5=35b1e053f109345542bb63b7f247fcf4 id_number: 10.1007/978-981-19-2300-5₆ full_text_status: none publication: Studies in Computational Intelligence volume: 1042 pagerange: 81-92 refereed: TRUE citation: AbuSalim, S.W.G. and Mostafa, S.A. and Mustapha, A. and Ibrahim, R. and Wahab, M.H.A. (2023) Identifying Cyberspace Usersâ�� Tendency in Blog Writing Using Machine Learning Algorithms. Studies in Computational Intelligence, 1042. pp. 81-92.