  We propose a graph-based mechanism to extract rich-emotion bearing patterns,
which fosters a deeper analysis of online emotional expressions, from a corpus.
The patterns are then enriched with word embeddings and evaluated through
several emotion recognition tasks. Moreover, we conduct analysis on the
emotion-oriented patterns to demonstrate its applicability and to explore its
properties. Our experimental results demonstrate that the proposed techniques
outperform most state-of-the-art emotion recognition techniques.
