Abstract
Sentiment analysis is the process of identifying and categorizing opinions computationally to determine the attitude expressed in the spoken or written text as positive, negative, or neutral. Negation analysis is the task of analyzing the negative opinions by identifying the scope of negation within a sentence and applying linguistic or grammatical rules of the language. In this paper, the rules for identifying the scope of negation within a sentence and the rules applicable to different negation categories are defined. An algorithm by the name SentiNeg has been proposed for processing negations at the sentence level. SentiNeg algorithm filters non-opinionated sentences from the data to avoid unnecessary processing. For opiniated sentences, the algorithm applies different linguistic or grammatical rules of the language to identify negative opinions. SentiNeg algorithm takes opinionated sentences as input and provides a detailed aspect-based summary of negative opinions that are expressed on the entity under analysis.
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