Inference of Personal Attributes from Tweets Using Machine Learning
This addresses the problem of inferring user demographics from social media data, but it is incremental as it applies existing methods to a specific domain.
The study tackled predicting personal attributes like gender, occupation, and age from tweets using machine learning, achieving 60-70% accuracy.
Using machine learning algorithms, including deep learning, we studied the prediction of personal attributes from the text of tweets, such as gender, occupation, and age groups. We applied word2vec to construct word vectors, which were then used to vectorize tweet blocks. The resulting tweet vectors were used as inputs for training models, and the prediction accuracy of those models was examined as a function of the dimension of the tweet vectors and the size of the tweet blacks. The results showed that the machine learning algorithms could predict the three personal attributes of interest with 60-70% accuracy.