Gender Prediction from Social Media Comments with Artificial Intelligence - Özer Çelik; Ahmet Faruk Aslan (Sakarya Üniversitesi Fen Bilimleri Enstitüsü Dergisi)
In the 21st century,which can be termed as artificial age of intelligence, machine learningtechniques that can become widespread and improve themselves can be given morequality services to humanity in many fields. As a result of these developments,nowadays many companies deliver their products and services to their customersvia social media accounts. But not every customer is interested in all productor service. Each customer's area of interest is different. Gender is one of themain reasons for this difference. If the gender of a social media user isdetermined correctly, the amount of sales may be increased by offering theappropriate products or services. The main aim of our study is an estimation ofgenders of the commenters thanks to machine learning techniques by analyzingthe comments of companies posting on Facebook. As a result of the study thegenders of the commenters were labelled according to the names by collectingthe comments from Facebook. The data set is divided into training and test dataas 70-30%. As a result of the study, it was seen that machine learning methodspredicted with similar accuracy rates, while the highest accuracy rate (74.13%)was obtained by logistic regression method.