Linguistic Reflexes of Well-Being and Happiness in Echo
Table 2: Number of Sentences for Train and Test
['[BOLD] Dataset', '[BOLD] Pos', '[BOLD] Neg', '[BOLD] Total']
We start with the 10354 posts from the echo corpus and map happiness scores between [1, 4] to negative, and scores between [6, 9] to positive. For posts labelled 5 by the experiencer, we categorize it as negative if its reflection score decreases to lower than 5, and positive if its reflection score increases. We label the rest of the 5s as neutral, and leave them aside. We then have 5997 positive posts and 3573 negative posts. We randomly sample 2868 posts as training data, and 478 as test data. We keep the rest of the 6224 posts untouched for future work. Then we split the posts into sentences.