Semantic vs. Syntactic tools in Sentiment Analysis

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Semantic vs. Syntactic tools in Sentiment Analysis
Politecnico Di Milano (CIS project) January 2013 Omar Zaky (782210) Amr rabiee (797617) Ahmed Mohamed Maged Mahmoud Ahmed (797379) ARTICLE INFORMATION Keywords: Sentiment analysis Semantic syntactic

ABSTRACT
Sentiment analysis is being of great importance day after day, with the increasing amount of similar user-generated data {in the form of reviews, blogs, etc.} online (Web 2.0), the need for automated tools for such analysis has increased recently. Thanks to the very speedy developing technology. Organizations are increasingly using the content in these media for decision making. For an organization, it may no longer be necessary to conduct surveys, opinion polls, and focus groups in order to gather public opinions because there is an abundance of such information publicly available. Due to these applications, industrial activities have flourished in recent years. Sentiment analysis applications have spread to almost every possible domain, from consumer products, services, healthcare, and financial services to social events and political elections. Sentiment analysis is relying heavily on the Semantic orientation of the words which is the science of the meaning that lies beneath words and an understanding of the relationships between words, and the syntactic identification which assumes that each linguistic element like a noun, a verb, etc. can have an intrinsic value of sentiment that is propagated through the syntactic structure of the parsed sentence This study is concerned with reviewing the latest used semantic and syntactical tools used for the subjectivity analysis and the sentiment analysis. We performed our analysis based on the existing literature review on that topic and we combined both the origin of this tools and their mechanisms with the state to art findings.

1.Introduction Sentiment analysis is being of great importance day after day, With the increasing amount of similar usergenerated data { in the form of reviews, blogs, etc} online, the need for automated tools for such analysis has increased recently. Thanks to the very speedy developing technology. Organizations are increasingly using the content in these media for decision making. For an organization, it may no longer be necessary to conduct surveys, opinion polls, and focus groups in order to gather public opinions because there is an abundance of such information publicly available.

Sentiment analysis is relying heavily on the Semantic orientation of the words which is the science of the meaning that lies beneath words and an understanding of the relationships between words, and the syntactic identification which assumes that each linguistic element like a noun, a verb, etc. can have an intrinsic value of sentiment that is propagated through the syntactic structure of the parsed sentence This study is concerned with reviewing the latest used semantic and syntactical tools used for the subjectivity analysis and the sentiment analysis. In the first section we will go through the sentiment analysis definition and then use this as an entry point to describe the different methods

and classifications for the semantic approaches. Then, define the syntactic approaches used and their mechanisms. The following section will discuss some already used semantic and syntactic features. Then we will conclude with the challenges and the further future studies needed for improving this considerably new science. 2. Sentiment analysis Sentiment analysis has received much attention over the past few years as a method of extracting useful knowledge from opinionated text (text with opinions or sentiments) .It aims to automatically detect subjective information contained in text, identify the sentiment polarity of this subjective information, and estimate the strength of the sentiment polarity.[6] Sentiment Analysis has many names. It’s often referred to as subjectivity analysis, opinion mining, and...
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