mission3 news
Abstract
In this work we use consumed text to infer Big5 personality inventories using data we have collected from the social media platform Reddit. We test our models on two datasets, sampled from participants who consumed either fiction content (N = 913) or news content(N = 213). We show that state-of-the-art models from a similar task using authored text do not translate well to this task, with average correlations of r = .06 between the model’s predictions and ground-truth personality inventory dimensions. We propose an alternate method of generating average personality labels for each piece of text consumed, under which our model achieves correlations as high as r = .34 when predicting personality from the text being read
