Sentence-based sentiment analysis with domain adaptation capability

Gezici, Gizem (2013) Sentence-based sentiment analysis with domain adaptation capability. [Thesis]

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Sentiment analysis aims to automatically estimate the sentiment in a given text as positive, objective or negative, possibly together with the strength of the sentiment. Polarity lexicons that indicate how positive or negative each term is, are often used as the basis of many sentiment analysis approaches. Domain-specific polarity lexicons are expensive and time-consuming to build; hence, researchers often use a general purpose or domainindependent lexicon as the basis of their analysis. In this work, we address two sub-tasks in sentiment analysis. We introduce a simple method to adapt a general purpose polarity lexicon to a specific domain. Subsequently, we propose new features to be used in a term polarity based approach to sentiment analysis. We consider different aspects of sentences, such as length, purity, irrealis content, subjectivity, and position within the opinionated text. This analysis is used to find sentences that may convey better information about the overall review polarity. Therefore, our work is also focused on the sentence-based sentiment analysis differently from the other works. Moreover, we worked on two distinct domains, hotel and Twitter with three different systems which are compared with the existing state-of-the-art approaches in the literature.
Item Type: Thesis
Uncontrolled Keywords: Sentiment analysis. -- Opinion mining. -- Domain adaptation. -- Lexicon-based. -- Sentence-based features. -- Duygu analizi. -- Düşünce madenciliği. -- Bağlam adaptasyonu. -- Veri sözlüğü temelli. -- Cümle temelli özellikler.
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK7800-8360 Electronics > TK7885-7895 Computer engineering. Computer hardware
Divisions: Faculty of Engineering and Natural Sciences > Academic programs > Computer Science & Eng.
Faculty of Engineering and Natural Sciences
Depositing User: IC-Cataloging
Date Deposited: 08 Oct 2015 11:23
Last Modified: 26 Apr 2022 10:05

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