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This thesis report is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2006.Cataloged from PDF version of thesis report.Includes bibliographical references (page 75).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.Altaf MahmudKazi Zubair AhmedB. Computer Science and Engineerin
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