We use SenticNet (Cambria et al., 2018) to normalize these emotion words (W = {w 1 , w 2 , .
two events with similar word embeddings may have similar embeddings despite that they are quite unrelated, for example, as shown in Figure 1 (b), "PersonX broke record" and "PersonY broke vase".