Title: 25 Tweets to Know You: A New Model to Predict Personality with Social Media,
Abstract: Predicting personality is essential for social applications supporting
human-centered activities, yet prior modeling methods with users written text
require too much input data to be realistically used in the context of social
media. In this work, we aim to drastically reduce the data requirement for
personality modeling and develop a model that is applicable to most users on
Twitter. Our model integrates Word Embedding features with Gaussian Processes
regression. Based on the evaluation of over 1.3K users on Twitter, we find that
our model achieves comparable or better accuracy than state of the art
techniques with 8 times fewer data.