#MeTooMA: Multi-Aspect Annotations of Tweets Related to the MeToo Movement
Table 6: Correlation coefficients and p-values for each pair of labels in the dataset.
['[BOLD] Label pair', '[BOLD] PCC', '[BOLD] p-PCC', '[BOLD] KCC', '[BOLD] p-KCC', '[BOLD] SCC', '[BOLD] p-SCC']
We conducted a simple experiment to understand the linguistic similarities (or lack thereof) for different pairs of class labels both within and across tasks. To this end, for each pair of labels, we converted the data into its tf-idf representation and then estimated Pearson, Spearman, and Kendall Tau correlation coefficients and also the corresponding p values. Overall, the correlation values seem to be on a lower end with maximum Pearson’s correlation value obtained for the label pair Justification - Support, maximum Kendall Tau’s correlation for Allegation - Support, and maximum Spearman’s correlation for Directed Hate - Generalized Hate. The correlations are statistically significant (p < 0.05) for three pairs of class labels: Directed Hate - Generalized Hate, Directed Hate - Opposition, Sarcasm - Opposition. Sarcasm and Allegation also have statistically significant p values for Pearson and Spearman correlations.