DEVELOPMENT OF A MACHINE LEARNING ALGORITHM TO PREDICT AUTHOR'S AGE FROM TEXT
Creators
- 1. Department of Computer Science, Faculty of Physical Sciences, Nnamdi Azikiwe University Awka, Anambra State, Nigeria.
- 2. Nwafor Orizu College of Eduation Nsugbe, Nigeria
- 3. Prototype Engineering Development Institute (PEDI), Ilesha, Osun State, Nigeria
Description
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 in natural language processing have made it possible to predict author’s age from text by 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%.
Files
29_IJRG19_A10_2762.pdf
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