In the late years sentiment analysis and its applications have reached growing popularity. Concerning this field of research, in the very late years machine learning and word representation learning derived from distributional semantics field (i.e. word embeddings) have proven to be very successful in performing sentiment analysis tasks. In this paper we describe a set of experiments, with the aim of evaluating the impact of word embedding-based features in sentiment analysis tasks.
Word embeddings in sentiment analysis
Dell'Orletta F
2018
Abstract
In the late years sentiment analysis and its applications have reached growing popularity. Concerning this field of research, in the very late years machine learning and word representation learning derived from distributional semantics field (i.e. word embeddings) have proven to be very successful in performing sentiment analysis tasks. In this paper we describe a set of experiments, with the aim of evaluating the impact of word embedding-based features in sentiment analysis tasks.| Campo DC | Valore | Lingua |
|---|---|---|
| dc.authority.anceserie | CEUR WORKSHOP PROCEEDINGS | - |
| dc.authority.anceserie | CEUR Workshop Proceedings | - |
| dc.authority.people | Petrolito R | it |
| dc.authority.people | Dell'Orletta F | it |
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| dc.collection.name | 04.01 Contributo in Atti di convegno | * |
| dc.contributor.appartenenza | Istituto di linguistica computazionale "Antonio Zampolli" - ILC | * |
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| dc.date.accessioned | 2024/02/21 02:44:59 | - |
| dc.date.available | 2024/02/21 02:44:59 | - |
| dc.date.issued | 2018 | - |
| dc.description.abstracteng | In the late years sentiment analysis and its applications have reached growing popularity. Concerning this field of research, in the very late years machine learning and word representation learning derived from distributional semantics field (i.e. word embeddings) have proven to be very successful in performing sentiment analysis tasks. In this paper we describe a set of experiments, with the aim of evaluating the impact of word embedding-based features in sentiment analysis tasks. | - |
| dc.description.affiliations | Università di Pisa, , Italy; Istituto di Linguistica Computazionale Antonio Zampolli (ILC-CNR), ItaliaNLP Lab., , Italy | - |
| dc.description.allpeople | Petrolito R.; Dell'Orletta F. | - |
| dc.description.allpeopleoriginal | Petrolito R.; Dell'Orletta F. | - |
| dc.description.fulltext | none | en |
| dc.description.numberofauthors | 1 | - |
| dc.identifier.doi | 10.4000/books.aaccademia.3589 | - |
| dc.identifier.scopus | 2-s2.0-85057752928 | - |
| dc.identifier.uri | https://hdl.handle.net/20.500.14243/392548 | - |
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| dc.language.iso | eng | - |
| dc.relation.conferencedate | 10-12/12/2018 | - |
| dc.relation.conferencename | 5th Italian Conference on Computational Linguistics (CLiC-it) | - |
| dc.relation.conferenceplace | Torino | - |
| dc.relation.volume | 2253 | - |
| dc.subject.keywords | Word Embeddings | - |
| dc.subject.keywords | Sentiment Analysis | - |
| dc.subject.singlekeyword | Word Embeddings | * |
| dc.subject.singlekeyword | Sentiment Analysis | * |
| dc.title | Word embeddings in sentiment analysis | en |
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| iris.scopus.extTitle | Word embeddings in sentiment analysis | - |
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| scopus.contributor.affiliation | Università di Pisa | - |
| scopus.contributor.affiliation | ItaliaNLP Lab. | - |
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| scopus.contributor.country | Italy | - |
| scopus.contributor.country | Italy | - |
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| scopus.contributor.name | Ruggero | - |
| scopus.contributor.name | Felice | - |
| scopus.contributor.subaffiliation | - | |
| scopus.contributor.subaffiliation | Istituto di Linguistica Computazionale Antonio Zampolli (ILC-CNR); | - |
| scopus.contributor.surname | Petrolito | - |
| scopus.contributor.surname | Dell'Orletta | - |
| scopus.date.issued | 2018 | * |
| scopus.description.abstracteng | In the late years sentiment analysis and its applications have reached growing popularity. Concerning this field of research, in the very late years machine learning and word representation learning derived from distributional semantics field (i.e. word embeddings) have proven to be very successful in performing sentiment analysis tasks. In this paper we describe a set of experiments, with the aim of evaluating the impact of word embedding-based features in sentiment analysis tasks. | * |
| scopus.description.allpeopleoriginal | Petrolito R.; Dell'Orletta F. | * |
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| scopus.title | Word embeddings in sentiment analysis | * |
| scopus.titleeng | Word embeddings in sentiment analysis | * |
| Appare nelle tipologie: | 04.01 Contributo in Atti di convegno | |
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