Occupation Prediction from Twitter Data

Today, the use of social media has become quite widespread. Among social media platforms, Twitter, now known as X, stands out with its number of users and abundance of data. This data can be used in many studies. In this study, it is aimed to predict occupation based on Turkish tweets. In the study, 5 datasets of different sizes were used. The tweets are evaluated and compared as single and pairwise. In the pre-processing step, different machine learning and deep learning methods and pre-trained models were tested using 2 different natural language processing libraries. Among the machine learning methods, the highest accuracy of 88% was obtained from the Logistic Regression model with pairwise tweet data, while the highest accuracy of 88% was obtained with the Multi-layer Perceptron from deep learning models. The BERT and "ytu-ce-cosmos/turkish-base-bert-uncased" developed by Yıldız Technical University COSMOS AI Research Team were used as pre-trained models. Although these models gave different results on different datasets, both of them achieved the highest success with a ratio of 89% on pairwise tweet data.