Pipelined model for classification of the processed tweets

Authors

  • B M. Bandgar

DOI:

https://doi.org/10.14419/ijet.v7i2.3.9962

Published:

2018-03-08

Keywords:

Unstructured models, Classification of Tweets, Opinion Mining

Abstract

The The extraction and processing of the real-time tweets is one of the challenging tasks. The processed tweets are classified using unstructured models. These showed no. of neutral tweets after the classification the tweets. Therefore, here pipelined unstructured model is developed the for the classification of tweets and explored to reduce the number of neutral tweets. It showed more reduction in the number of neutral tweets as compared to other unstructured model such as the SWNC model results.

References

[1] Bandgar B. M. and Binod Kumar, Real time extraction and processing of social tweets, International Journal of Computer Science and Engineering, E-ISSN No.-2347-2693,, Vol.3 No.3, (2015) , pp. 1- 6.

[2] Bandgar B. M. and Dr. Sheeja Azije, Analysis of real time social tweets for opinion mining, International Journal of Applied Engineering Research ISSN No. 0973-4562 Vol. 11 No. 2, (2016), pp. 1404 -1407.

[3] https://www.twitter.com

[4] R. Machedon, W. Rand, Y. Joshi, Automatic Classification of Social Media Messaging using Multi-Dimensional Sentiment Analysis and Crowd sourcing, http://dx.doi.org/10.2139/ssrn.2244353 (Available at SSRN: http://ssrn.com/abstract=2244353), 2013.

[5] Farhan Hassan Khan et. al. , TOM: Twitter opinion mining framework using hybrid classification scheme, Decision Support Systems, (2013), http://dx.doi.org/10.1016/j.dss.2013.09.004

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