Finding  emotions  in  text  is  an  area  of  research  with  wide-ranging 
applications. We describe an emotion annotation task of identifying emotion category, emotion intensity and the words/phrases that indicate emotion in text. We introduce the annotation scheme and present results of an annotation agreement study on a corpus of blog posts. The average inter-annotator agreement on labeling a sentence as emotion or non-emotion was 0.76. The agreement on emotion categories was in the range 0.6 to 0.79; for emotion indicators, it was  0.66. Preliminary results of emotion classification experiments show the accuracy of 73.89%, significantly above the baseline.