T4SA is intended for training and testing image sentiment analysis approaches. It contains little less than a million tweets, corresponding to about 1.5M images. We initially collected about 3.4M tweets corresponding to about 4M images. We classified the sentiment polarity of the texts (as described in Section 4) and we selected the tweets having the most confident textual sentiment predictions to build our Twitter for Sentiment Analysis (T4SA) dataset. The dataset is publicly available at: http://www.t4sa.it/
T4SA: Twitter for Sentiment Analysis
Carrara F;Cimino A;Cresci S;Dell'Orletta F;Falchi F;Vadicamo L;Tesconi M
2017
Abstract
T4SA is intended for training and testing image sentiment analysis approaches. It contains little less than a million tweets, corresponding to about 1.5M images. We initially collected about 3.4M tweets corresponding to about 4M images. We classified the sentiment polarity of the texts (as described in Section 4) and we selected the tweets having the most confident textual sentiment predictions to build our Twitter for Sentiment Analysis (T4SA) dataset. The dataset is publicly available at: http://www.t4sa.it/| Campo DC | Valore | Lingua |
|---|---|---|
| dc.authority.orgunit | Istituto di informatica e telematica - IIT | - |
| dc.authority.orgunit | Istituto di linguistica computazionale "Antonio Zampolli" - ILC | - |
| dc.authority.orgunit | Istituto di Scienza e Tecnologie dell'Informazione "Alessandro Faedo" - ISTI | - |
| dc.authority.people | Carrara F | it |
| dc.authority.people | Cimino A | it |
| dc.authority.people | Cresci S | it |
| dc.authority.people | Dell'Orletta F | it |
| dc.authority.people | Falchi F | it |
| dc.authority.people | Vadicamo L | it |
| dc.authority.people | Tesconi M | it |
| dc.collection.id.s | aa7ef5cb-003d-421c-b2c8-870fc44d02e5 | * |
| dc.collection.name | 05.10 Dataset | * |
| dc.contributor.appartenenza | Istituto di Scienza e Tecnologie dell'Informazione "Alessandro Faedo" - ISTI | * |
| dc.contributor.appartenenza | Istituto di informatica e telematica - IIT | * |
| dc.contributor.appartenenza | Istituto di linguistica computazionale "Antonio Zampolli" - ILC | * |
| dc.contributor.appartenenza.mi | 912 | * |
| dc.contributor.appartenenza.mi | 918 | * |
| dc.contributor.appartenenza.mi | 973 | * |
| dc.date.accessioned | 2024/02/20 12:51:57 | - |
| dc.date.available | 2024/02/20 12:51:57 | - |
| dc.date.issued | 2017 | - |
| dc.description.abstracteng | T4SA is intended for training and testing image sentiment analysis approaches. It contains little less than a million tweets, corresponding to about 1.5M images. We initially collected about 3.4M tweets corresponding to about 4M images. We classified the sentiment polarity of the texts (as described in Section 4) and we selected the tweets having the most confident textual sentiment predictions to build our Twitter for Sentiment Analysis (T4SA) dataset. The dataset is publicly available at: http://www.t4sa.it/ | - |
| dc.description.affiliations | CNR-ISTI, Pisa, Italy; CNR-ILC, Pisa, Italy; CNR-IIT, Pisa, Italy; CNR-ILC, Pisa, Italy; CNR-ISTI, Pisa, Italy; CNR-ISTI, Pisa, Italy; CNR-IIT, Pisa, Italy; | - |
| dc.description.allpeople | Carrara, F; Cimino, A; Cresci, S; Dell'Orletta, F; Falchi, F; Vadicamo, L; Tesconi, M | - |
| dc.description.allpeopleoriginal | Carrara F.; Cimino A.; Cresci S.; Dell'Orletta F.; Falchi F.; Vadicamo L.; Tesconi M. | - |
| dc.description.fulltext | none | en |
| dc.description.numberofauthors | 7 | - |
| dc.identifier.uri | https://hdl.handle.net/20.500.14243/411838 | - |
| dc.identifier.url | http://www.t4sa.it/ | - |
| dc.language.iso | eng | - |
| dc.miur.last.status.update | 2025-01-31T10:09:02Z | * |
| dc.subject.keywords | social media | - |
| dc.subject.keywords | sentiment analysis | - |
| dc.subject.keywords | image analysis | - |
| dc.subject.keywords | image sentiment analysis | - |
| dc.subject.keywords | deep learning | - |
| dc.subject.keywords | multimedia sentiment analysis | - |
| dc.subject.keywords | dataset | - |
| dc.subject.keywords | tweets | - |
| dc.subject.singlekeyword | social media | * |
| dc.subject.singlekeyword | sentiment analysis | * |
| dc.subject.singlekeyword | image analysis | * |
| dc.subject.singlekeyword | image sentiment analysis | * |
| dc.subject.singlekeyword | deep learning | * |
| dc.subject.singlekeyword | multimedia sentiment analysis | * |
| dc.subject.singlekeyword | dataset | * |
| dc.subject.singlekeyword | tweets | * |
| dc.title | T4SA: Twitter for Sentiment Analysis | en |
| dc.type.driver | info:eu-repo/semantics/other | - |
| dc.type.full | 05 Altro::05.10 Dataset | it |
| dc.type.miur | 295 | - |
| dc.ugov.descaux1 | 429823 | - |
| iris.orcid.lastModifiedDate | 2024/09/16 09:00:48 | * |
| iris.orcid.lastModifiedMillisecond | 1726470048134 | * |
| iris.sitodocente.maxattempts | 1 | - |
| Appare nelle tipologie: | 05.10 Dataset | |
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