Psychological State in Text: A Limitation of Sentiment Analysis
Table 3: Correlations between measurement and model score.
['[ITALIC] ρ', 'PANAS POS', 'PANAS NEG', 'PANAS', 'CES-D']
We first train TextCNN model in collected movie review data and see its performance. On 9-level polarity, TextCNN performs 41.32% on accuracy. We can ensure that TextCNN performs well on our data in that our data has 9-level polarity whereas state-of-arts model performs 52.0% on 5-level polarity. After checking the performance, we evaluate book report data; 3 of them are 1 point, 4 of them are 2 points, 2 of them are 3 points, 3 of them are 4 points, 1 of them is 5 points, 29 of them are 8 points. Finally, we investigate the relationship between the scores and psychological measurements.