@inproceedings{baric-etal-2023-target,
title = "Target Two Birds With One {ST}o{N}e: Entity-Level Sentiment and Tone Analysis in {C}roatian News Headlines",
author = "Bari{\'c}, Ana and
Majer, Laura and
Duki{\'c}, David and
Grbe{\v{s}}a-zenzerovi{\'c}, Marijana and
Snajder, Jan",
editor = "Piskorski, Jakub and
Marci{\'n}czuk, Micha{\l} and
Nakov, Preslav and
Ogrodniczuk, Maciej and
Pollak, Senja and
P{\v{r}}ib{\'a}{\v{n}}, Pavel and
Rybak, Piotr and
Steinberger, Josef and
Yangarber, Roman",
booktitle = "Proceedings of the 9th Workshop on Slavic Natural Language Processing 2023 (SlavicNLP 2023)",
month = may,
year = "2023",
address = "Dubrovnik, Croatia",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2023.bsnlp-1.10",
doi = "10.18653/v1/2023.bsnlp-1.10",
pages = "78--85",
abstract = "Sentiment analysis is often used to examine how different actors are portrayed in the media, and analysis of news headlines is of particular interest due to their attention-grabbing role. We address the task of entity-level sentiment analysis from Croatian news headlines. We frame the task as targeted sentiment analysis (TSA), explicitly differentiating between sentiment toward a named entity and the overall tone of the headline. We describe SToNe, a new dataset for this task with sentiment and tone labels. We implement several neural benchmark models, utilizing single- and multi-task training, and show that TSA can benefit from tone information. Finally, we gauge the difficulty of this task by leveraging dataset cartography.",
}
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%0 Conference Proceedings
%T Target Two Birds With One SToNe: Entity-Level Sentiment and Tone Analysis in Croatian News Headlines
%A Barić, Ana
%A Majer, Laura
%A Dukić, David
%A Grbeša-zenzerović, Marijana
%A Snajder, Jan
%Y Piskorski, Jakub
%Y Marcińczuk, Michał
%Y Nakov, Preslav
%Y Ogrodniczuk, Maciej
%Y Pollak, Senja
%Y Přibáň, Pavel
%Y Rybak, Piotr
%Y Steinberger, Josef
%Y Yangarber, Roman
%S Proceedings of the 9th Workshop on Slavic Natural Language Processing 2023 (SlavicNLP 2023)
%D 2023
%8 May
%I Association for Computational Linguistics
%C Dubrovnik, Croatia
%F baric-etal-2023-target
%X Sentiment analysis is often used to examine how different actors are portrayed in the media, and analysis of news headlines is of particular interest due to their attention-grabbing role. We address the task of entity-level sentiment analysis from Croatian news headlines. We frame the task as targeted sentiment analysis (TSA), explicitly differentiating between sentiment toward a named entity and the overall tone of the headline. We describe SToNe, a new dataset for this task with sentiment and tone labels. We implement several neural benchmark models, utilizing single- and multi-task training, and show that TSA can benefit from tone information. Finally, we gauge the difficulty of this task by leveraging dataset cartography.
%R 10.18653/v1/2023.bsnlp-1.10
%U https://aclanthology.org/2023.bsnlp-1.10
%U https://doi.org/10.18653/v1/2023.bsnlp-1.10
%P 78-85
Markdown (Informal)
[Target Two Birds With One SToNe: Entity-Level Sentiment and Tone Analysis in Croatian News Headlines](https://aclanthology.org/2023.bsnlp-1.10) (Barić et al., BSNLP 2023)
ACL