Abstract:
Since Internet has become the leading source of information for the users,
flames or abusive messages have also become the prominent factors of time
wasting for retrieving information. Moreover, a text can contain factual
information as well as abusive or insulting contents. This paper describes a
new approach for an automated system to distinguish between information
and personal attack containing insulting or abusive messages in a given
document. In NLP, flames or abusive messages are considered as extreme
subjective language, which refers to detect personal opinions or emotions in
a news article. Insulting or abusive messages are viewed as extreme subset
of the subjective language because of its extreme nature. We defined some
rules to extract the semantic information of a given sentence from the
general semantic structure of that sentence.