Amrita_student at SemEval-2018 Task 1: Distributed Representation of Social Media Text for Affects in Tweets

Nidhin A Unnithan, Shalini K., Barathi Ganesh H. B., Anand Kumar M, Soman K. P.


Abstract
In this paper we did an analysis of “Affects in Tweets” which was one of the task conducted by semeval 2018. Task was to build a model which is able to do regression and classification of different emotions from the given tweets data set. We developed a base model for all the subtasks using distributed representation (Doc2Vec) and applied machine learning techniques for classification and regression. Distributed representation is an unsupervised algorithm which is capable of learning fixed length feature representation from variable length texts. Machine learning techniques used for regression is ’Linear Regression’ while ’Random Forest Tree’ is used for classification purpose. Empirical results obtained for all the subtasks by our model are shown in this paper.
Anthology ID:
S18-1047
Volume:
Proceedings of The 12th International Workshop on Semantic Evaluation
Month:
June
Year:
2018
Address:
New Orleans, Louisiana
Venue:
*SEMEVAL
SIGs:
SIGLEX | SIGSEM
Publisher:
Association for Computational Linguistics
Note:
Pages:
319–323
Language:
URL:
https://www.aclweb.org/anthology/S18-1047
DOI:
10.18653/v1/S18-1047
Bib Export formats:
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PDF:
http://aclanthology.lst.uni-saarland.de/S18-1047.pdf