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Authors: Nikolaos Nodarakis 1 ; Spyros Sioutas 2 ; Athanasios K. Tsakalidis 1 and Giannis Tzimas 3

Affiliations: 1 University of Patras, Greece ; 2 Ionian University, Greece ; 3 Technological Educational Institute of Western Greece, Greece

Keyword(s): Big Data, Bloom Filters, Classification, MapReduce, Hadoop, Sentiment Analysis, Twitter.

Related Ontology Subjects/Areas/Topics: Distributed and Parallel Applications ; Internet Technology ; Web Information Systems and Technologies

Abstract: Sentiment analysis on Twitter data has attracted much attention recently. People tend to express their feelings freely, which makes Twitter an ideal source for accumulating a vast amount of opinions towards a wide diversity of topics. In this paper, we develop a novel method to harvest sentiment knowledge in the MapReduce framework. Our algorithm exploits the hashtags and emoticons inside a tweet, as sentiment labels, and proceeds to a classification procedure of diverse sentiment types in a parallel and distributed manner. Moreover, we utilize Bloom filters to compact the storage size of intermediate data and boost the performance of our algorithm. Through an extensive experimental evaluation, we prove that our solution is efficient, robust and scalable and confirm the quality of our sentiment identification.

CC BY-NC-ND 4.0

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Paper citation in several formats:
Nodarakis, N.; Sioutas, S.; Tsakalidis, A. and Tzimas, G. (2016). MR-SAT: A MapReduce Algorithm for Big Data Sentiment Analysis on Twitter. In Proceedings of the 12th International Conference on Web Information Systems and Technologies - Volume 1: WEBIST; ISBN 978-989-758-186-1; ISSN 2184-3252, SciTePress, pages 140-147. DOI: 10.5220/0005850401400147

@conference{webist16,
author={Nikolaos Nodarakis. and Spyros Sioutas. and Athanasios K. Tsakalidis. and Giannis Tzimas.},
title={MR-SAT: A MapReduce Algorithm for Big Data Sentiment Analysis on Twitter},
booktitle={Proceedings of the 12th International Conference on Web Information Systems and Technologies - Volume 1: WEBIST},
year={2016},
pages={140-147},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005850401400147},
isbn={978-989-758-186-1},
issn={2184-3252},
}

TY - CONF

JO - Proceedings of the 12th International Conference on Web Information Systems and Technologies - Volume 1: WEBIST
TI - MR-SAT: A MapReduce Algorithm for Big Data Sentiment Analysis on Twitter
SN - 978-989-758-186-1
IS - 2184-3252
AU - Nodarakis, N.
AU - Sioutas, S.
AU - Tsakalidis, A.
AU - Tzimas, G.
PY - 2016
SP - 140
EP - 147
DO - 10.5220/0005850401400147
PB - SciTePress