Tools of Opinion Mining

Tools of Opinion Mining

Neha Gupta (Manav Rachna International Institute of Research and Studies, India) and Siddharth Verma (Manav Rachna International Institute of Research and Studies, India)
Copyright: © 2019 |Pages: 25
DOI: 10.4018/978-1-5225-6117-0.ch009
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Today's generation express their views and opinions publicly. For any organization or for individuals, this feedback is very crucial to improve their products and services. This huge volume of reviews can be analyzed by opinion mining (also known as semantic analysis). It is an emerging field for researchers that aims to distinguish the emotions expressed within the reviews, classifying them into positive or negative opinions, and summarizing it into a form that is easily understood by users. The idea of opinion mining and sentiment analysis tool is to process a set of search results for a given item based on the quality and features. Research has been conducted to mine opinions in form of document, sentence, and feature level sentiment analysis. This chapter examines how opinion mining is moving to the sentimental reviews of Twitter data, comments used in Facebook on pictures, videos, or Facebook statuses. Thus, this chapter discusses an overview of opinion mining in detail with the techniques and tools.
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Process Model Of Opinion Mining

The following process model describes steps, methods and tools to find, extract and analyze web data with regard to their sentiment orientation:

  • 1.

    Selection of relevant data source

  • 2.

    Selection of relevant method and tool to analyze the data

  • 3.

    Pre-processing and pre-structuring of the contents on basis of the chosen methods

  • 4.

    Transformation of the text in standard and further processed structure

  • 5.

    Analyzing the content in relation to its semantic orientation

  • 6.

    Evaluation of the methods and tools

Table 1 outlines commonly used methods and tools for each process step.

Table 1.
Methods and tools for various steps of opinion mining
StepMethod (examples)Tools (examples)
Selection of relevant data1. Information retrieval on Web
2. Relevance Index
1. WebCrawler
2. RSS feeds,
3. APIs for gathering data
PreprocessingThesaurus, Ontologies,
Tokenizer, Stemmer,
Screen scrapper
2. Alchemy API
TransformationPart of speech tagger,
Sentence splitter,
Orthographic co-references
1. Tree Tagger
2. Sentence splitter,
3. Orthographic co-references
AnalysisClassification methods
based on document or
sentence level
1. Opinion Observer
2. Rapid Miner
EvaluationManual classification of
sentiment orientation
and feedback

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