  We use referential translation machines (RTMs) to identify the similarity
between an attribute and two words in English by casting the task as machine
translation performance prediction (MTPP) between the words and the attribute
word and the distance between their similarities for Task 10 with stacked RTM
models. RTMs are also used to predict the intensity of the structure and
content in tweets in English, Arabic, and Spanish in Task 1 where MTPP is
between the tweets and the set of words for the emotion selected from WordNet
affect emotion lists. Stacked RTM models obtain encouraging results in both.
