• Corpus ID: 235313377

EmoDNN: Understanding emotions from short texts through a deep neural network ensemble

@article{Kamran2021EmoDNNUE,
  title={EmoDNN: Understanding emotions from short texts through a deep neural network ensemble},
  author={Sara Kamran and Raziyeh Zall and Mohammad Reza Kangavari and Saeid Hosseini and Sana Rahmani and Wenlan Hua},
  journal={ArXiv},
  year={2021},
  volume={abs/2106.01706}
}
The latent knowledge in the emotions and the opinions of the individuals that are manifested via social networks are crucial to numerous applications including social management, dynamical processes, and public security. Affective computing, as an interdisciplinary research field, linking artificial intelligence to cognitive inference, is capable to exploit emotion-oriented knowledge from brief contents. The textual contents convey hidden information such as personality and cognition about… 
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