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Authors: Sarah Alhumoud ; Tarfa Albuhairi and Wejdan Alohaideb

Affiliation: Al-Imam Muhammad Ibn Saud Islamic University, Saudi Arabia

Keyword(s): Sentiment Analysis, Data Mining, Machine Learning, Supervised Approach, Hybrid Learning.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Business Analytics ; Clustering and Classification Methods ; Computational Intelligence ; Concept Mining ; Data Analytics ; Data Engineering ; Evolutionary Computing ; Knowledge Discovery and Information Retrieval ; Knowledge-Based Systems ; Machine Learning ; Mining Text and Semi-Structured Data ; Soft Computing ; Symbolic Systems

Abstract: Harvesting meaning out of massively increasing data could be of great value for organizations. Twitter is one of the biggest public and freely available data sources. This paper presents a Hybrid learning implementation to sentiment analysis combining lexicon and supervised approaches. Analysing Arabic, Saudi dialect Twitter tweets to extract sentiments toward a specific topic. This was done using a dataset consisting of 3000 tweets collected in three domains. The obtained results confirm the superiority of the hybrid learning approach over the supervised and unsupervised approaches.

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Paper citation in several formats:
Alhumoud, S. ; Albuhairi, T. and Alohaideb, W. (2015). Hybrid Sentiment Analyser for Arabic Tweets using R. In Proceedings of the 7th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2015) - KDIR; ISBN 978-989-758-158-8; ISSN 2184-3228, SciTePress, pages 417-424. DOI: 10.5220/0005616204170424

@conference{kdir15,
author={Sarah Alhumoud and Tarfa Albuhairi and Wejdan Alohaideb},
title={Hybrid Sentiment Analyser for Arabic Tweets using R},
booktitle={Proceedings of the 7th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2015) - KDIR},
year={2015},
pages={417-424},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005616204170424},
isbn={978-989-758-158-8},
issn={2184-3228},
}

TY - CONF

JO - Proceedings of the 7th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2015) - KDIR
TI - Hybrid Sentiment Analyser for Arabic Tweets using R
SN - 978-989-758-158-8
IS - 2184-3228
AU - Alhumoud, S.
AU - Albuhairi, T.
AU - Alohaideb, W.
PY - 2015
SP - 417
EP - 424
DO - 10.5220/0005616204170424
PB - SciTePress

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