Emotion Mining in Social Media Data-Reference-Cited by-同舟云学术

Emotion Mining in Social Media Data

Published:2019 Issue: Volume:159 Page:58-66
ISSN:1877-0509
Container-title:Procedia Computer Science
language:en
Short-container-title:Procedia Computer Science

Author:

Ranganathan Jaishree,Tzacheva Angelina

Publisher

Elsevier BV

Subject

General Engineering

Reference32 articles.

1. Kde-affect at semeval-2018 task 1: Estimation of affects in tweet by using convolutional neural network for n-gram;Aono;in: Proceedings of The 12th International Workshop on Semantic Evaluation,2018

2. Bagavathi, A., Rao, V., Tzacheva, A.A., 2018. Data distribution method for scalable actionable pattern mining, in: Proceedings of the First International Conference on Data Science, E-learning and Information Systems, ACM. p. 3.

3. Rule based systems in distributed environment: Survey;Bagavathi;in: Proceedings of International Conference on Cloud Computing and Applications (CCA17), 3rd World Congress on Electrical Engineering and Computer Systems and Science (EECSS’17),2017

4. Dardzinska, A., 2012. Action rules mining. volume 468. Springer.

5. Lt3 at semeval-2018 task 1: A classifier chain to detect emotions in tweets, in: SemEval-2018;De Bruyne,2018

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