User Gender Classification Based on Twitter Profile Using Machine Learning

In the recent past, there has been a swift rise in the count of people accessing social media sites like twitter in many countries across the globe. This led to a surge in interest to identify gender based on their profile. This study could be beneficial for many fields such as legal inquisition, analysing election polls, recommendations of e-commerce platforms, survey results, marketing, and forensics. Men and women have unique styles of expressing their views in tweets. Based on these distinctions between both men and women, this research aims to categorise the gender of a Twitter profile. This investigation will deep dive into the usage of various Natural Language Tool Kit (NLTK) libraries that process on textual attributes of the dataset. This study provides a comparative analysis of the accuracies obtained after applying various algorithms of machine learning. The usage of predominant textual attributes is majorly concentrated in this study.