Analysis and Comparison of Deep Learning Networks for Supporting Sentiment Mining in Text Corpora

Giosue' Lo Bosco, Alfredo Cuzzocrea, Giovanni Pilato, Daniele Schicchi

Research output: Chapter in Book/Report/Conference proceedingConference contribution


In this paper, we tackle the problem of the irony and sarcasm detection for the Italian language to contribute to the enrichment of the sentiment analysis field. We analyze and compare five deep-learning systems. Results show the high suitability of such systems to face the problem by achieving 93% of F1-Score in the best case. Furthermore, we briefly analyze the model architectures in order to choose the best compromise between performances and complexity.
Original languageEnglish
Title of host publicationThe 22nd International Conference on Information Integration and Web-based Applications & Services
Number of pages6
Publication statusPublished - 2020

All Science Journal Classification (ASJC) codes

  • Human-Computer Interaction
  • Computer Networks and Communications
  • Computer Vision and Pattern Recognition
  • Software

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