@inproceedings{petee-palmer-2020-untling,
title = "{UNTL}ing at {S}em{E}val-2020 Task 11: Detection of Propaganda Techniques in {E}nglish News Articles",
author = "Petee, Maia and
Palmer, Alexis",
editor = "Herbelot, Aurelie and
Zhu, Xiaodan and
Palmer, Alexis and
Schneider, Nathan and
May, Jonathan and
Shutova, Ekaterina",
booktitle = "Proceedings of the Fourteenth Workshop on Semantic Evaluation",
month = dec,
year = "2020",
address = "Barcelona (online)",
publisher = "International Committee for Computational Linguistics",
url = "https://aclanthology.org/2020.semeval-1.243",
doi = "10.18653/v1/2020.semeval-1.243",
pages = "1847--1852",
abstract = "Our system for the PropEval task explores the ability of semantic features to detect and label propagandistic rhetorical techniques in English news articles. For Subtask 2, labeling identified propagandistic fragments with one of fourteen technique labels, our system attains a micro-averaged F1 of 0.40; in this paper, we take a detailed look at the fourteen labels and how well our semantically-focused model detects each of them. We also propose strategies to fill the gaps.",
}
<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="petee-palmer-2020-untling">
<titleInfo>
<title>UNTLing at SemEval-2020 Task 11: Detection of Propaganda Techniques in English News Articles</title>
</titleInfo>
<name type="personal">
<namePart type="given">Maia</namePart>
<namePart type="family">Petee</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Alexis</namePart>
<namePart type="family">Palmer</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<originInfo>
<dateIssued>2020-12</dateIssued>
</originInfo>
<typeOfResource>text</typeOfResource>
<relatedItem type="host">
<titleInfo>
<title>Proceedings of the Fourteenth Workshop on Semantic Evaluation</title>
</titleInfo>
<name type="personal">
<namePart type="given">Aurelie</namePart>
<namePart type="family">Herbelot</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Xiaodan</namePart>
<namePart type="family">Zhu</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Alexis</namePart>
<namePart type="family">Palmer</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Nathan</namePart>
<namePart type="family">Schneider</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Jonathan</namePart>
<namePart type="family">May</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Ekaterina</namePart>
<namePart type="family">Shutova</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<originInfo>
<publisher>International Committee for Computational Linguistics</publisher>
<place>
<placeTerm type="text">Barcelona (online)</placeTerm>
</place>
</originInfo>
<genre authority="marcgt">conference publication</genre>
</relatedItem>
<abstract>Our system for the PropEval task explores the ability of semantic features to detect and label propagandistic rhetorical techniques in English news articles. For Subtask 2, labeling identified propagandistic fragments with one of fourteen technique labels, our system attains a micro-averaged F1 of 0.40; in this paper, we take a detailed look at the fourteen labels and how well our semantically-focused model detects each of them. We also propose strategies to fill the gaps.</abstract>
<identifier type="citekey">petee-palmer-2020-untling</identifier>
<identifier type="doi">10.18653/v1/2020.semeval-1.243</identifier>
<location>
<url>https://aclanthology.org/2020.semeval-1.243</url>
</location>
<part>
<date>2020-12</date>
<extent unit="page">
<start>1847</start>
<end>1852</end>
</extent>
</part>
</mods>
</modsCollection>
%0 Conference Proceedings
%T UNTLing at SemEval-2020 Task 11: Detection of Propaganda Techniques in English News Articles
%A Petee, Maia
%A Palmer, Alexis
%Y Herbelot, Aurelie
%Y Zhu, Xiaodan
%Y Palmer, Alexis
%Y Schneider, Nathan
%Y May, Jonathan
%Y Shutova, Ekaterina
%S Proceedings of the Fourteenth Workshop on Semantic Evaluation
%D 2020
%8 December
%I International Committee for Computational Linguistics
%C Barcelona (online)
%F petee-palmer-2020-untling
%X Our system for the PropEval task explores the ability of semantic features to detect and label propagandistic rhetorical techniques in English news articles. For Subtask 2, labeling identified propagandistic fragments with one of fourteen technique labels, our system attains a micro-averaged F1 of 0.40; in this paper, we take a detailed look at the fourteen labels and how well our semantically-focused model detects each of them. We also propose strategies to fill the gaps.
%R 10.18653/v1/2020.semeval-1.243
%U https://aclanthology.org/2020.semeval-1.243
%U https://doi.org/10.18653/v1/2020.semeval-1.243
%P 1847-1852
Markdown (Informal)
[UNTLing at SemEval-2020 Task 11: Detection of Propaganda Techniques in English News Articles](https://aclanthology.org/2020.semeval-1.243) (Petee & Palmer, SemEval 2020)
ACL