Please use this identifier to cite or link to this item: http://repository.unizik.edu.ng/handle/123456789/582
Title: DEVELOPMENT OF A MACHINE LEARNING ALGORITHM TO PREDICT AUTHOR’S AGE FROM TEXT
Authors: Asogwa, D.C
Anigbogu, S.O
Anigbogu, G.N
Efozia, F.N
Keywords: Author Profiling
Machine Learning
Binary Classification
Natural Language Processing
Issue Date: Oct-2019
Publisher: International Journal Of Research Granthaalayah
Citation: International Journal Of Research Granthaalayah, Vol.7 (Iss.10)
Abstract: Author's age prediction is the task of determining the author's age by studying the texts written by them. The prediction of author’s age can be enlightening about the different trends, opinions social and political views of an age group. Marketers always use this to encourage a product or a service to an age group following their conveyed interests and opinions. Methodologies natural language processing have made it possible to predict author’s age from text examining the variation of linguistic characteristics. Also, many machine learning algorithms have been used in author’s age prediction. However, in social networks, computational linguists are challenged with numerous issues just as machine learning techniques are performance driven with its own challenges in realistic scenarios. This work developed a model that can predict author's age from text with a machine learning algorithm (Naïve Bayes) using three types of features namely, content based, style based and topic based. The trained model gave a prediction accuracy of 80%.
Description: Scholarly Work
URI: DOI: 10.5281/zenodo.3532022
http://repository.unizik.edu.ng/handle/123456789/582
ISSN: e-2350-0530, p- 2394-3629
Appears in Collections:Scholarly Works

Files in This Item:
File Description SizeFormat 
29_IJRG19_A10_2762.pdf526.65 kBAdobe PDFView/Open


Items in UnizikSpace are protected by copyright, with all rights reserved, unless otherwise indicated.