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• W2805679416 abstract "This paper describes the NeuroSent system that participated in SemEval 2018 Task 3. Our system takes a supervised approach that builds on neural networks and word embeddings. Word embeddings were built by starting from a repository of user generated reviews. Thus, they are specific for sentiment analysis tasks. Then, tweets are converted in the corresponding vector representation and given as input to the neural network with the aim of learning the different semantics contained in each emotion taken into account by the SemEval task. The output layer has been adapted based on the characteristics of each subtask. Preliminary results obtained on the provided training set are encouraging for pursuing the investigation into this direction." @default.
• W2805679416 created "2018-06-13" @default.
• W2805679416 creator A5069303169 @default.
• W2805679416 date "2018-01-01" @default.
• W2805679416 modified "2023-09-26" @default.
• W2805679416 title "NEUROSENT-PDI at SemEval-2018 Task 3: Understanding Irony in Social Networks Through a Multi-Domain Sentiment Model" @default.
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• W2805679416 doi "https://doi.org/10.18653/v1/s18-1083" @default.
• W2805679416 hasPublicationYear "2018" @default.
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