Int. J. of Cloud Computing   »   2016 Vol.5, No.1/2

 

 

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Title: Opinion mining of microblog texts on Hadoop ecosystem

 

Authors: Muhammed Akif Ağca; Şenol Ataç; Mehmet Mert Yücesan; Yusuf Gökhan Küçükayan; Ahmet Murat Özbayoğlu; Erdoğan Doğdu

 

Addresses:
Department of Computer Engineering, TOBB University of Economics and Technology, Ankara, Turkey
Department of Computer Engineering, TOBB University of Economics and Technology, Ankara, Turkey
Department of Computer Engineering, TOBB University of Economics and Technology, Ankara, Turkey
Department of Computer Engineering, TOBB University of Economics and Technology, Ankara, Turkey
Department of Computer Engineering, TOBB University of Economics and Technology, Ankara, Turkey
Department of Computer Engineering, TOBB University of Economics and Technology, Ankara, Turkey

 

Abstract: Opinion mining started getting more traction due to the increasing popularity of Twitter and similar social network platforms that are producing fast and real-time responses to social events. It is a very challenging area since it is difficult, if not impossible, to identify general public sentiment towards events, entities, etc., using opinion mining techniques over huge numbers of tweets and messages automatically. In this study we present our opinion mining techniques on tweet data with early results. We apply sentiment scoring and clustering algorithms using Hadoop ecosystem for parallel processing. We classify tweets by tagging them as positive, negative, and neutral as a result.

 

Keywords: opinion mining; sentiment scoring; distributed computing; parallel processing; large scale application development; microblogs; microblog texts; Hadoop; social networks; public sentiment; Twitter; tweet data; clustering algorithms; tweets.

 

DOI: 10.1504/IJCC.2016.075096

 

Int. J. of Cloud Computing, 2016 Vol.5, No.1/2, pp.79 - 90

 

Submission date: 29 Sep 2014
Date of acceptance: 11 Mar 2015
Available online: 02 Mar 2016

 

 

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