Evidence map›Paper›PMID 37275533›Full record

ArticleFrontiers in artificial intelligence2023

Who are the haters? A corpus-based demographic analysis of authors of hate speech.

Lisa Hilte, Ilia Markov, Nikola Ljubešić, Darja Fišer, Walter Daelemans

Open access · goldAbstract read
In one paragraph

Article in Frontiers in artificial intelligence, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.9field-weighted citation impact, top 22% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed, 5 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 4 institutions in 3 countries.

Lisa HilteCLIPS, Department of Linguistics, Faculty of Arts, University of Antwerp, Antwerp, Belgium.
Ilia MarkovCLTL, Department of Language, Literature and Communication, Faculty of Humanities, Vrije Universiteit Amsterdam, Amsterdam, Netherlands.
Nikola LjubešićDepartment of Knowledge Technologies, Institut Jožef Stefan (IJS), Ljubljana, Slovenia.
Darja FišerDepartment of Knowledge Technologies, Institut Jožef Stefan (IJS), Ljubljana, Slovenia.
Walter DaelemansCLIPS, Department of Linguistics, Faculty of Arts, University of Antwerp, Antwerp, Belgium.
University of Antwerp · BEInstitute of Contemporary History · SIJožef Stefan Institute · SIVrije Universiteit Amsterdam · NL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: We examine the profiles of hate speech authors in a multilingual dataset of Facebook reactions to news posts discussing topics related to migrants and the LGBT+ community. The included languages are English, Dutch, Slovenian, and Croatian. Methods: First, all utterances were manually annotated as hateful or acceptable speech. Next, we used binary logistic regression to inspect how the production of hateful comments is impacted by authors' profiles (i.e., their age, gender, and language). Results: Our results corroborate previous findings: in all four languages, men produce more hateful comments than women, and people produce more hate speech as they grow older. But our findings also add important nuance to previously attested tendencies: specific age and gender dynamics vary slightly in different languages or cultures, suggesting that distinct (e.g., socio-political) realities are at play. Discussion: Finally, we discuss why author demographics are important in the study of hate speech: the profiles of prototypical "haters" can be used for hate speech detection, for sensibilization on and for counter-initiatives to the spread of (online) hatred.

Indexed as

agedemographicsgenderhate speechlanguage area

Identifiers

PMID37275533
PMCPMC10235607
OpenAlexW4377097735

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.