Distinguishing between factual information and insulting or abusive messages bearing words or phrases in news articles
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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.