Original: This paperdescribes a corpus annotation process  to support the identification of hate speech and offensive language in social media.
Revised: The understanding of an offense is subjective and people may have different opinions about the offensiveness of a comment. Also, offenses and hate speech may occur through sarcasm, which hides the real intention of the comment and makes the decision of the annotators more confusing. Therefore, provide a well-structured annotation process is crucial to a better understanding of hate speech and offensive language phenomena, as well as supply better performance for machine learning classifiers. In this paper, we describe a corpus annotation process to support the identification of hate speech and offensive language in social media.
Edit intent: meaning-changed