  Personality can be defined as the combination of behavior, emotion,
motivation, and thoughts that aim at describing various aspects of human
behavior based on a few stable and measurable characteristics. Considering the
fact that our personality has a remarkable influence in our daily life,
automatic recognition of a person's personality attributes can provide many
essential practical applications in various aspects of cognitive science. deep
learning based method for the task of personality recognition from text is
proposed in this paper. Among various deep neural networks, Convolutional
Neural Networks (CNN) have demonstrated profound efficiency in natural language
processing and especially personality detection. Owing to the fact that various
filter sizes in CNN may influence its performance, we decided to combine CNN
with AdaBoost, a classical ensemble algorithm, to consider the possibility of
using the contribution of various filter lengths and gasp their potential in
the final classification via combining various classifiers with respective
filter size using AdaBoost. Our proposed method was validated on the Essay
dataset by conducting a series of experiments and the empirical results
demonstrated the superiority of our proposed method compared to both machine
learning and deep learning methods for the task of personality recognition.
