Opinion extraction and classification of real time Facebook Status

Mr. Akash Shrivastava

Opinion extraction and classification of real time Facebook Status

Mr. Akash Shrivastava * §

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Graphic Era University, Dehradun, India.

Opinion extraction and classification of real time Facebook Status

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Abstract

Social media like Facebook today are not only just a website. They are now become much popular communication tool for internet users. It is a medium through which users belonging to any of category, profession can make their comments. These all comments have contained some features along with it. These comments or status are really useful which are actually viewed as their ‘OPINIONS’. Opinions are really important while we need to analyze any of product, topic, discussion and whatever which will require some user opinions to draw some inferences and conclusions from them. Social media plays an important role for this intention. In this paper we focused on facebook statuses, which we can view as opinions of users or their reaction on concern we want to analyze. We develop tool status puller that automatically collects random facebook statuses. Then we make classifier that performs classifications on that corpus collected from facebook. Our classifier is able to extract three features GOOD, BAD and AVERGAE from that statuses respectively. As per classifier results we perform evaluations experiments which further can be work for feature mining of user opinions on facebook. It’s pure new and unique technique proposed in the field of opinion mining.

References

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Reference Format

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Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

No ethics committee approval was required for this article type.

Data Availability

Not applicable for this article.

How to Cite This Article

Mr. Akash Shrivastava. 1970. "Opinion extraction and classification of real time Facebook Status". Global Journal of Computer Science and Technology GJCST Volume 12 (GJCST Volume 12 Issue 8).

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GJCST Volume 12 Issue 8

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Journal Specifications

Crossref Journal DOI 10.17406/gjcst

Print ISSN 0975-4350

e-ISSN 0975-4172

Keywords

Classification Data mining facebook status mining Opinion mining support vector machine text categorization web mining

Classification

GJCST Classification H.3.5

Submission ReceivedApril 6, 2012
Peer Review Double Blind
Handling Editor
Accepted May 5, 2012
Published May 15, 2012

Version of record

v1.2

Issue date

April 21, 2012

Language

English

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Article Matrices

Total Score: 142

Country: India

Subject: Global Journal of Computer Science and Technology

Authors: Mr. Akash Shrivastava, Bhasker Pant (PhD/Dr. count: 0)

View Count (all-time): 368

Total Views (Real + Logic): 4464

Total Downloads (simulated): 314

Publish Date: 2012 05, Tue

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Total Views: 4.5K

Total Downloads: 314

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