Evaluation of Most Popular Sentiment Lexicons Coverage on Various Datasets-Reference-Cited by-同舟云学术

Evaluation of Most Popular Sentiment Lexicons Coverage on Various Datasets

Published:2019 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 2019 2nd International Conference on Sensors, Signal and Image Processing - SSIP 2019
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Author:

Miazga Justyna¹,Hachaj Tomasz¹

Affiliation:

1. Pedagogical University of Krakow, Institute of Computer Science, Krakow, Poland

Publisher

ACM Press

Reference13 articles.

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3. V. Kumar and S. Minz, "Mood classifiaction of lyrics using SentiWordNet," 2013 International Conference on Computer Communication and Informatics, Coimbatore, 2013, pp. 1--5. DOI= 10.1109/ICCCI.2013.6466307

4. M. Wöllmer et al., "YouTube Movie Reviews: Sentiment Analysis in an Audio-Visual Context," in IEEE Intelligent Systems, vol. 28, no. 3, pp. 46--53, May-June 2013. DOI= 10.1109/MIS.2013.34

5. Dey, Nilanjan & Borah, Samarjeet & Ashour, Amira S. & Babo, Rosalina. 2018. Social Network Analytics - Computational Research Methods and Techniques.

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