Open Access

ARTICLE

Depression Intensity Classification from Tweets Using FastText Based Weighted Soft Voting Ensemble

Muhammad Rizwan^1,2, Muhammad Faheem Mushtaq¹, Maryam Rafiq², Arif Mehmood³, Isabel de la Torre Diez⁴, Monica Gracia Villar^5,6,7, Helena Garay^5,8,9, Imran Ashraf^10,*

1 Department of Artificial Intelligence, The Islamia University of Bahawalpur, Bahawalnagar, 63100, Pakistan
2 Department of Information Technology, Khwaja Fareed University of Engineering and IT, RYKhan, 64200, Pakistan
3 Department of Computer Science & Information Technology, The Islamia University of Bahawalpur, Bahawalnagar, 63100, Pakistan
4 Department of Signal Theory and Communications and Telematic Engineering, Unviersity of Valladolid, Paseo de Belén 15, Valladolid, 47011, Spain
5 Faculty of Social Science and Humanities, Universidad Europea del Atlántico Isabel Torres 21, Santander, 39011, Spain
6 Department of Project Management, Universidad Internacional Iberoamericana, Campeche, 24560, México
7 Fundación Universitaria Internacional de Colombia, Bogotá, 111611, Colombia
8 Universidad Internacional Iberoamericana, Arecibo, Puerto Rico, 00613, USA
9 Universidade Internacional do Cuanza, Cuito, 46703, Angola
10 Department of Information and Communication Engineering, Yeungnam University, Gyeongsan, 38541, South Korea

* Corresponding Author: Imran Ashraf. Email: