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Bootstrapping Technique + Embeddings = Emotional Corpus Annotated Automatically

  • Lea Canales
  • Carlo Strapparava
  • Ester Boldrini
  • Patricio Matínez-Barco
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10341)

Abstract

Detecting depression or personality traits, tutoring and student behaviour systems, or identifying cases of cyber-bulling are a few of the wide range of the applications, in which the automatic detection of emotion is crucial. This task can contribute to the benefit of business, society, politics or education. The main objective of our research is focused on the improvement of the supervised emotion detection systems developed so far, through the definition and implementation of a technique to annotate large scale English emotional corpora automatically and with high standards of reliability. Our proposal is based on a bootstrapping process made up two main steps: the creation of the seed using NRC Emotion Lexicon and its extension employing the distributional semantic similarity through words embeddings. The results obtained are promising and allow us to confirm the soundness of the bootstrapping technique combined with the word embedding to label emotional corpora automatically.

Keywords

Sentiment analysis Emotion detection Emotional corpus Bootstrapping Word embedding 

Notes

Acknowledgment

This research has been supported by the FPI grant (BES-2013-065950) and the research stay grant (EEBB-I-15-10108) from the Spanish Ministry of Science and Innovation. It has also funded by the Spanish Government (DIGITY ref. TIN2015-65136-C02-2-R) and the Valencian Government (grant no. PROMETEOII/2014/001).

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Lea Canales
    • 1
  • Carlo Strapparava
    • 2
  • Ester Boldrini
    • 1
  • Patricio Matínez-Barco
    • 1
  1. 1.University of AlicanteAlicanteSpain
  2. 2.Fondazione Bruno KesslerTrentoItaly

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