Search results for "sarcasm detection"
showing 3 items of 3 documents
Effectiveness of Data-Driven Induction of Semantic Spaces and Traditional Classifiers for Sarcasm Detection
2019
Irony and sarcasm are two complex linguistic phenomena that are widely used in everyday language and especially over the social media, but they represent two serious issues for automated text understanding. Many labeled corpora have been extracted from several sources to accomplish this task, and it seems that sarcasm is conveyed in different ways for different domains. Nonetheless, very little work has been done for comparing different methods among the available corpora. Furthermore, usually, each author collects and uses their own datasets to evaluate his own method. In this paper, we show that sarcasm detection can be tackled by applying classical machine learning algorithms to input te…
Sviluppi della Intelligenza Computazionale: l'esempio del Sarcasm Detection
2016
Dopo un periodo prolungato in cui vigeva uno scarto persistente tra l’ottimismo dato dai grandi proclami di ricerca e la scarsità e frammentarietà di risultati veri e tangibili, viviamo (finalmente) nell’era delle grandi conquiste dell’Intelligenza Artificiale
Analysis and Comparison of Deep Learning Networks for Supporting Sentiment Mining in Text Corpora
2020
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.