  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.
