Sentiment analysis is an automatic way to determine that whether opinions of people about a subject are favorable or unfavorable. One of the most important sub tasks in sentiment analysis is to determine the sequence of words affected by negation. Most of the existing sentiment analysis systems used traditional methods based on static window and punctuation marks to determine the scope of negat...

Automatic detection of linguistic negation in free text is a critical need for many text processing applications, including sentiment analysis. This paper presents a negation detection system based on a conditional random field modeled using features from an English dependency parser. The scope of negation detection is limited to explicit rather than implied negations within single sentences. A...

Negation is often found more frequent in dialogue than commonly written texts, such as literary texts. Furthermore, the scope and focus of negation depends on context in dialogues than other forms of texts. Existing negation datasets have focused on non-dialogue texts such as literary texts where the scope and focus of negation is normally present within the same sentence where the negation is ...

Abstract Frame semantics for negation on the Australian Plan accommodates many different negations, but it falls short accommodating subminimal when language contains conjunction and disjunction. In this paper, I will present a multi-relational frame –multi-incompatibility semantics– that can accommodate negation. first argue multi-incompatibility frames are in accordance with philosophical mot...