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    <abstract>Emotions are a way of expressing human sentiments. In the modern era, social media is a platform where we convey our emotions. These emotions can be joy, anger, sadness and fear. Understanding the emotions from the written sentences is an interesting part in knowing about the writer. In the amount of digital language shared through social media, a considerable amount of data reflects the sentiment or emotion towards some product, person and organization. Since these texts are from users with diverse social aspects, these texts can be used to enrich the application related to the business intelligence. More than the sentiment, identification of intensity of the sentiment will enrich the performance of the end application. In this paper we experimented the intensity prediction as a text classification problem that evaluates the distributed representation text using aggregated sum and dimensionality reduction of the glove vectors of the words present in the respective texts .</abstract>
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%0 Conference Proceedings
%T TeamCEN at SemEval-2018 Task 1: Global Vectors Representation in Emotion Detection
%A George, Anon
%A Ganesh H. B., Barathi
%A Kumar M, Anand
%A K P, Soman
%Y Apidianaki, Marianna
%Y Mohammad, Saif M.
%Y May, Jonathan
%Y Shutova, Ekaterina
%Y Bethard, Steven
%Y Carpuat, Marine
%S Proceedings of the 12th International Workshop on Semantic Evaluation
%D 2018
%8 June
%I Association for Computational Linguistics
%C New Orleans, Louisiana
%F george-etal-2018-teamcen
%X Emotions are a way of expressing human sentiments. In the modern era, social media is a platform where we convey our emotions. These emotions can be joy, anger, sadness and fear. Understanding the emotions from the written sentences is an interesting part in knowing about the writer. In the amount of digital language shared through social media, a considerable amount of data reflects the sentiment or emotion towards some product, person and organization. Since these texts are from users with diverse social aspects, these texts can be used to enrich the application related to the business intelligence. More than the sentiment, identification of intensity of the sentiment will enrich the performance of the end application. In this paper we experimented the intensity prediction as a text classification problem that evaluates the distributed representation text using aggregated sum and dimensionality reduction of the glove vectors of the words present in the respective texts .
%R 10.18653/v1/S18-1050
%U https://aclanthology.org/S18-1050
%U https://doi.org/10.18653/v1/S18-1050
%P 334-338

Markdown (Informal)

[TeamCEN at SemEval-2018 Task 1: Global Vectors Representation in Emotion Detection](https://aclanthology.org/S18-1050) (George et al., SemEval 2018)

• TeamCEN at SemEval-2018 Task 1: Global Vectors Representation in Emotion Detection (George et al., SemEval 2018)

ACL

• Anon George, Barathi Ganesh H. B., Anand Kumar M, and Soman K P. 2018. TeamCEN at SemEval-2018 Task 1: Global Vectors Representation in Emotion Detection. In Proceedings of the 12th International Workshop on Semantic Evaluation, pages 334–338, New Orleans, Louisiana. Association for Computational Linguistics.