@inproceedings{vieira-figueira-2026-emotion,
title = "Emotion and Information Disorder in {NLP}: A Systematic Mapping and Benchmark Blueprint",
author = "Vieira, Renatha and
Figueira, Alvaro",
editor = "Frenda, Simona and
Stranisci, Marco Antonio and
Ashraf, Shaina and
Ren, Ada and
Konstas, Ioannis and
Naseem, Usman",
booktitle = "Proceedings of the 1st Workshop on Information Disorder ({I}n{D}or) @ {LREC} 2026",
month = may,
year = "2026",
address = "Palma de Mallorca, Spain",
publisher = "ELRA Language Resources Association (ELRA)",
url = "https://aclanthology.org/2026.indor-1.8/",
doi = "10.63317/3xyqihqhsxkj",
pages = "77--84",
ISBN = "978-2-493814-87-6",
abstract = "Online misinformation research in NLP has expanded rapidly, including approaches that model affective signals such as sentiment, discrete emotions, and emotion dynamics. However, the Information Disorder framework distinguishes misinformation, disinformation, and malinformation along dimensions of intention, harm, and contextual dependence, which are rarely operationalised in current datasets, tasks, and evaluation protocols. We provide a systematic mapping of 82 studies at the intersection of Information Disorder and emotion-aware NLP (51 model papers, 7 dataset papers, 24 survey/theory papers). Across empirical works (58), veracity-centric supervision dominates (72.4{\%} binary labels), while explicit intention and harm variables appear in only 1.7{\%} each. Evaluation relies mostly on random splits (79.3{\%}), limiting robustness to source and temporal shifts. Emotion is represented in 43.1{\%} of model papers, mostly as static features, with emotion dynamics and audience emotion rare. Based on these findings, we propose an operational taxonomy aligned with Information Disorder and a benchmark blueprint specifying tasks, annotation variables, split strategies, and evaluation protocols to support theory-grounded, comparable progress."
}<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="vieira-figueira-2026-emotion">
<titleInfo>
<title>Emotion and Information Disorder in NLP: A Systematic Mapping and Benchmark Blueprint</title>
</titleInfo>
<name type="personal">
<namePart type="given">Renatha</namePart>
<namePart type="family">Vieira</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Alvaro</namePart>
<namePart type="family">Figueira</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<originInfo>
<dateIssued>2026-05</dateIssued>
</originInfo>
<typeOfResource>text</typeOfResource>
<relatedItem type="host">
<titleInfo>
<title>Proceedings of the 1st Workshop on Information Disorder (InDor) @ LREC 2026</title>
</titleInfo>
<name type="personal">
<namePart type="given">Simona</namePart>
<namePart type="family">Frenda</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Marco</namePart>
<namePart type="given">Antonio</namePart>
<namePart type="family">Stranisci</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Shaina</namePart>
<namePart type="family">Ashraf</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Ada</namePart>
<namePart type="family">Ren</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Ioannis</namePart>
<namePart type="family">Konstas</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Usman</namePart>
<namePart type="family">Naseem</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<originInfo>
<publisher>ELRA Language Resources Association (ELRA)</publisher>
<place>
<placeTerm type="text">Palma de Mallorca, Spain</placeTerm>
</place>
</originInfo>
<genre authority="marcgt">conference publication</genre>
<identifier type="isbn">978-2-493814-87-6</identifier>
</relatedItem>
<abstract>Online misinformation research in NLP has expanded rapidly, including approaches that model affective signals such as sentiment, discrete emotions, and emotion dynamics. However, the Information Disorder framework distinguishes misinformation, disinformation, and malinformation along dimensions of intention, harm, and contextual dependence, which are rarely operationalised in current datasets, tasks, and evaluation protocols. We provide a systematic mapping of 82 studies at the intersection of Information Disorder and emotion-aware NLP (51 model papers, 7 dataset papers, 24 survey/theory papers). Across empirical works (58), veracity-centric supervision dominates (72.4% binary labels), while explicit intention and harm variables appear in only 1.7% each. Evaluation relies mostly on random splits (79.3%), limiting robustness to source and temporal shifts. Emotion is represented in 43.1% of model papers, mostly as static features, with emotion dynamics and audience emotion rare. Based on these findings, we propose an operational taxonomy aligned with Information Disorder and a benchmark blueprint specifying tasks, annotation variables, split strategies, and evaluation protocols to support theory-grounded, comparable progress.</abstract>
<identifier type="citekey">vieira-figueira-2026-emotion</identifier>
<identifier type="doi">10.63317/3xyqihqhsxkj</identifier>
<location>
<url>https://aclanthology.org/2026.indor-1.8/</url>
</location>
<part>
<date>2026-05</date>
<extent unit="page">
<start>77</start>
<end>84</end>
</extent>
</part>
</mods>
</modsCollection>
%0 Conference Proceedings
%T Emotion and Information Disorder in NLP: A Systematic Mapping and Benchmark Blueprint
%A Vieira, Renatha
%A Figueira, Alvaro
%Y Frenda, Simona
%Y Stranisci, Marco Antonio
%Y Ashraf, Shaina
%Y Ren, Ada
%Y Konstas, Ioannis
%Y Naseem, Usman
%S Proceedings of the 1st Workshop on Information Disorder (InDor) @ LREC 2026
%D 2026
%8 May
%I ELRA Language Resources Association (ELRA)
%C Palma de Mallorca, Spain
%@ 978-2-493814-87-6
%F vieira-figueira-2026-emotion
%X Online misinformation research in NLP has expanded rapidly, including approaches that model affective signals such as sentiment, discrete emotions, and emotion dynamics. However, the Information Disorder framework distinguishes misinformation, disinformation, and malinformation along dimensions of intention, harm, and contextual dependence, which are rarely operationalised in current datasets, tasks, and evaluation protocols. We provide a systematic mapping of 82 studies at the intersection of Information Disorder and emotion-aware NLP (51 model papers, 7 dataset papers, 24 survey/theory papers). Across empirical works (58), veracity-centric supervision dominates (72.4% binary labels), while explicit intention and harm variables appear in only 1.7% each. Evaluation relies mostly on random splits (79.3%), limiting robustness to source and temporal shifts. Emotion is represented in 43.1% of model papers, mostly as static features, with emotion dynamics and audience emotion rare. Based on these findings, we propose an operational taxonomy aligned with Information Disorder and a benchmark blueprint specifying tasks, annotation variables, split strategies, and evaluation protocols to support theory-grounded, comparable progress.
%R 10.63317/3xyqihqhsxkj
%U https://aclanthology.org/2026.indor-1.8/
%U https://doi.org/10.63317/3xyqihqhsxkj
%P 77-84
Markdown (Informal)
[Emotion and Information Disorder in NLP: A Systematic Mapping and Benchmark Blueprint](https://aclanthology.org/2026.indor-1.8/) (Vieira & Figueira, InDor 2026)
ACL