SACAM - A Model for Describing and Classifying Sentiment Analysis Methods

Aleksander Waloszek, Wojciech Waloszek

Abstract

In this paper we introduce SACAM — a model for describing and classifying sentiment analysis (SA) methods. The model focuses on the knowledge used during processing textual opinions. SACAM was designed to create informative descriptions of SA methods (or classes of SA methods) and is strongly integrated with its accompanying graphical notation suited for presenting the descriptions in diagrammatical form. The paper discusses applications of SACAM and shows directions of its further development.

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Paper Citation


in Harvard Style

Waloszek A. and Waloszek W. (2017). SACAM - A Model for Describing and Classifying Sentiment Analysis Methods . In Proceedings of the 9th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART, ISBN 978-989-758-220-2, pages 196-206. DOI: 10.5220/0006199901960206


in Bibtex Style

@conference{icaart17,
author={Aleksander Waloszek and Wojciech Waloszek},
title={SACAM - A Model for Describing and Classifying Sentiment Analysis Methods},
booktitle={Proceedings of the 9th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,},
year={2017},
pages={196-206},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006199901960206},
isbn={978-989-758-220-2},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 9th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,
TI - SACAM - A Model for Describing and Classifying Sentiment Analysis Methods
SN - 978-989-758-220-2
AU - Waloszek A.
AU - Waloszek W.
PY - 2017
SP - 196
EP - 206
DO - 10.5220/0006199901960206