Personality prediction of Twitter users with Logistic Regression Classifier learned using Stochastic Gradient Descent
Iosr Journals, Sharma Kanupriya, Amanpreet Kaur · Figshare · 2015
Twitter is a popular social media platform with millions of users. The tweets shared by these users have recently attracted the attention of researchers from diverse fields. In this research, we focus primarily on predicting user's personality from the analysis of tweets shared by the user. An associative study of different research works done in personality prediction shows that different techniques have been used to predict a user's personality from tweets but there are certain shortcomings which still need to be addressed. In the introduction section we have given the gist of personality prediction with Twitter research. In the next section we provide the importance and framework of predicting a user's personality with Twitter. In the consecutive section, literature survey, we have discussed briefly about the different research ideas in context to personality prediction with a side by side overview of various resources, tools and machine learning algorithms that were used alongside their potential and limitations, followed by research gap, which provides different fields of possibilities to which can be rectified to improve the efficiency of predicting personality with machine learning algorithms. Finally, a new approach is proposed to predict personality with new insights to predict personality on crucial factors such as scalability and counter measures to improve the research based on previous work by using a Logistic Regression Classifier with parameter regularization using stochastic gradient descent.