  Emojis have become ubiquitous in digital communication, due to their visual
appeal as well as their ability to vividly convey human emotion, among other
factors. The growing prominence of emojis in social media and other instant
messaging also leads to an increased need for systems and tools to operate on
text containing emojis. In this study, we assess this support by considering
test sets of tweets with emojis, based on which we perform a series of
experiments investigating the ability of prominent NLP and text processing
tools to adequately process them. In particular, we consider tokenization,
part-of-speech tagging, as well as sentiment analysis. Our findings show that
many tools still have notable shortcomings when operating on text containing
emojis.
