Opinion Mining (also known as Sentiment Analysis [2, 3]) is a sub- eld of text mining in which the main task is to extract opinions from content generated by Web users.

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Sentiment analysis and opinion mining mainly focuses on opinions which express or imply positive or negative sentiments. Although linguistics and natural language processing (NLP) have a long history, little research had been done about people's opinions and sentiments

L. Dini and G. Mazzini, "Opinion classification through information extraction," in Proceedings of the Conference on Data Mining Methods and Databases for Engineering, Finance and Other Fields (Data Mining), pp. 299-310, 2002.

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The output of such opinion mining is a feature-based opinion summary or aspect-based opinion summary. The commonly known sentiment classification is a sub-task. Our current work is in two main areas, which reflect two kinds of opinions (or evaluations)

Opinion definition is - a view, judgment, or appraisal formed in the mind about a particular matter. How to use opinion in a sentence. Synonym Discussion of opinion. a view, judgment, or appraisal formed in the mind about a particular matter; approval, esteem… See the full definition.

Data mining is an interdisciplinary subfield of computer science with an overall goal to extract information (with intelligent methods) from a data set and transform the information into a comprehensible structure for further use.

Typically, textual information is available as unstructured data, which require processing so that data mining algorithms can handle such data; this processing is known as the pre-processing step in the overall text mining process. This paper aims at analyzing the strong impact that the pre ...

Extracting Product Features and Opinions from Reviews Ana-Maria Popescu and Oren Etzioni ... OPINE, an unsupervised information-extraction system which mines re-views in order to build a model of im-portant product features, their evalu-ation by reviewers, and their relative ... lem of "opinion mining" has seen increasing attention over the ...

In this chapter, we only focus on mining opinions which indicate positive or negative sentiments. The task is technically challenging and practically very useful. For example, businesses always want to find public or consumer opinions on their products and services.

opinion mining and sentiment analysis, which deals with the computational treatment of opinion, sentiment, and subjectivity in text, has thus occurred at least in part as a direct response to the surge of interest in new systems that deal directly with opinions as a first-class object.

information, e.g., information retrieval, Web search, and many other text mining and natural language processing tasks. Little work has been done on the processing of opinions until only recently.

Mining opinion components from unstructured reviews: A review Khairullah Khan a,*, Baharum Baharudin a, Aurnagzeb Khan b, Ashraf Ullah b a Computer and Information Sciences Department, Universiti Teknologi, PETRONAS, Malaysia b Institute of Engineering and Computing Sciences, University of Science & Technology Bannu, Pakistan Received 31 August 2012; revised 31 May 2013; …

Sentiment analysis or opinion mining is the computational study of people's opinions, appraisals, attitudes, and emotions toward entities, individuals, issues, events, topics and their attributes.

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Advantages and Disadvantages of Data Mining. Data mining is an important part of knowledge discovery process that we can analyze an enormous set of data and get hidden and useful knowledge. Data mining is applied effectively not only in the business environment but also in other fields such as weather forecast, medicine, transportation ...

Opinion mining (sometimes known as sentiment analysis or emotion AI) refers to the use of natural language processing, text analysis, computational linguistics, and biometrics to systematically identify, extract, quantify, and study affective states and subjective information.

When you want to show whose opinion you are giving, you can use an expression such as 'in my opinion', 'in Sarah's opinion', or 'in the opinion of the voters...'. In my opinion, there are four key problems that have to be addressed.

Mar 20, 2018· That's the question raised after a former employee of a data mining firm that worked for Donald Trump's presidential campaign alleged the company used Facebook to bombard specific individuals with ...

Information Fusion is the field charged with researching efficient methods for transforming information from different sources into a single coherent representation, and therefore can be used to guide fusion processes in Opinion Mining.

Opinion mining is a type of natural language processing for tracking the mood of the public about a particular product. Opinion mining, which is also called sentiment analysis, involves building a system to collect and categorize opinions about a product.

Opinion mining is an interesting area of research because of its applications in various fields. Collecting opinions of people about products and about social and political events and problems through the Web is becoming increasingly popular every day.

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As the prevalence of social media on the Internet, opinion mining has become an essential approach to analyzing so many data. Various applications appear in a wide range of industrial domains.

Mining or Sentiment Analysis is a Natural Language Processing and Information Extraction task that identifies the user's views or opinions explained in the form of positive, negative or neutral

A Survey of Data Mining Techniques for Social Network Analysis Mariam Adedoyin-Olowe 1, ... information, news and opinion of other users on diverse subject matters. The heavy ... Data mining techniques have been found to be capable of handling the

Web opinion mining aims to extract, summarize, and track various aspects of subjective information on the Web. Mining subjective information enables traditional information retrieval (IR) systems to retrieve more data from human viewpoints and provide information with finer granularity.