MultiEmotions-it: A new dataset for opinion polarity and emotion analysis for Italian

Rachele Sprugnoli

doi:10.4000/books.aaccademia.8910

MultiEmotions-it: A new dataset for opinion polarity and emotion analysis for Italian

Rachele Sprugnoli^*

^*Corresponding author

Università Cattolica del Sacro Cuore

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

This paper1 presents a new linguistic resource for Italian, called MultiEmotions-It, containing comments to music videos and advertisements posted on YouTube and Facebook. These comments are manually annotated according to four different dimensions: i.e., relatedness, opinion polarity, emotions and sarcasm. For the annotation of emotions we adopted the Plutchik’s model taking into account both basic and complex emotions, i.e. dyads.

Original language	English
Title of host publication	Proceedings of the Seventh Italian Conference on Computational Linguistics (CLiC-it 2020)
Pages	402-408
Number of pages	7
DOIs	https://doi.org/10.4000/books.aaccademia.8910
Publication status	Published - 2020
Event	7th Italian Conference on Computational Linguistics, CLiC-it 2020 - online Duration: 1 Mar 2021 → 3 Mar 2021

Conference

Conference	7th Italian Conference on Computational Linguistics, CLiC-it 2020
City	online
Period	1/3/21 → 3/3/21

Keywords

emotion analysis
sentiment analysis

Access to Document

10.4000/books.aaccademia.8910

Cite this

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title = "MultiEmotions-it: A new dataset for opinion polarity and emotion analysis for Italian",

abstract = "This paper1 presents a new linguistic resource for Italian, called MultiEmotions-It, containing comments to music videos and advertisements posted on YouTube and Facebook. These comments are manually annotated according to four different dimensions: i.e., relatedness, opinion polarity, emotions and sarcasm. For the annotation of emotions we adopted the Plutchik{\textquoteright}s model taking into account both basic and complex emotions, i.e. dyads.",

keywords = "emotion analysis, sentiment analysis, emotion analysis, sentiment analysis",

author = "Rachele Sprugnoli",

year = "2020",

doi = "10.4000/books.aaccademia.8910",

language = "English",

isbn = "979-12-80136-28-2",

pages = "402--408",

booktitle = "Proceedings of the Seventh Italian Conference on Computational Linguistics (CLiC-it 2020)",

note = "7th Italian Conference on Computational Linguistics, CLiC-it 2020 ; Conference date: 01-03-2021 Through 03-03-2021",

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TY - GEN

T1 - MultiEmotions-it: A new dataset for opinion polarity and emotion analysis for Italian

AU - Sprugnoli, Rachele

PY - 2020

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N2 - This paper1 presents a new linguistic resource for Italian, called MultiEmotions-It, containing comments to music videos and advertisements posted on YouTube and Facebook. These comments are manually annotated according to four different dimensions: i.e., relatedness, opinion polarity, emotions and sarcasm. For the annotation of emotions we adopted the Plutchik’s model taking into account both basic and complex emotions, i.e. dyads.

AB - This paper1 presents a new linguistic resource for Italian, called MultiEmotions-It, containing comments to music videos and advertisements posted on YouTube and Facebook. These comments are manually annotated according to four different dimensions: i.e., relatedness, opinion polarity, emotions and sarcasm. For the annotation of emotions we adopted the Plutchik’s model taking into account both basic and complex emotions, i.e. dyads.

KW - emotion analysis

KW - sentiment analysis

KW - emotion analysis

KW - sentiment analysis

UR - http://hdl.handle.net/10807/165687

UR - http://ceur-ws.org/vol-2769/paper_08.pdf

U2 - 10.4000/books.aaccademia.8910

DO - 10.4000/books.aaccademia.8910

M3 - Conference contribution

SN - 979-12-80136-28-2

SP - 402

EP - 408

BT - Proceedings of the Seventh Italian Conference on Computational Linguistics (CLiC-it 2020)

T2 - 7th Italian Conference on Computational Linguistics, CLiC-it 2020

Y2 - 1 March 2021 through 3 March 2021

ER -

MultiEmotions-it: A new dataset for opinion polarity and emotion analysis for Italian

Abstract

Conference

Keywords

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