<!DOCTYPE article PUBLIC "-//NLM//DTD JATS (Z39.96) Journal Archiving and Interchange DTD v1.0 20120330//EN" "JATS-archivearticle1.dtd">
<article xmlns:xlink="http://www.w3.org/1999/xlink">
  <front>
    <journal-meta />
    <article-meta>
      <title-group>
        <article-title>SteRHeotypes Project. Detecting and Countering Ethnic Stereotypes emerging from Italian, Spanish and French Racial hoaxes</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <string-name>Francesca D'Errico</string-name>
          <email>francesca.derrico@uniba.it</email>
          <xref ref-type="aff" rid="aff2">2</xref>
          <xref ref-type="aff" rid="aff5">5</xref>
        </contrib>
        <contrib contrib-type="author">
          <string-name>Cristina Bosco</string-name>
          <email>cristina.bosco@unito.it</email>
          <xref ref-type="aff" rid="aff2">2</xref>
          <xref ref-type="aff" rid="aff6">6</xref>
        </contrib>
        <contrib contrib-type="author">
          <string-name>Marinella Paciello</string-name>
          <email>marinella.paciello@uninettunouniversity.net</email>
          <xref ref-type="aff" rid="aff2">2</xref>
          <xref ref-type="aff" rid="aff3">3</xref>
        </contrib>
        <contrib contrib-type="author">
          <string-name>Farah Benamara</string-name>
          <email>farah.benamara@irit.fr</email>
          <xref ref-type="aff" rid="aff0">0</xref>
          <xref ref-type="aff" rid="aff1">1</xref>
          <xref ref-type="aff" rid="aff2">2</xref>
        </contrib>
        <contrib contrib-type="author">
          <string-name>Paolo Giovanni Cicirelli</string-name>
          <email>paolo.cicirelli@uniba.it</email>
          <xref ref-type="aff" rid="aff2">2</xref>
          <xref ref-type="aff" rid="aff5">5</xref>
        </contrib>
        <contrib contrib-type="author">
          <string-name>Viviana Patti</string-name>
          <email>viviana.patti@unito.it</email>
          <xref ref-type="aff" rid="aff2">2</xref>
          <xref ref-type="aff" rid="aff6">6</xref>
        </contrib>
        <contrib contrib-type="author">
          <string-name>Véronique Moriceau</string-name>
          <email>veronique.moriceau@irit.fr</email>
          <xref ref-type="aff" rid="aff1">1</xref>
          <xref ref-type="aff" rid="aff2">2</xref>
        </contrib>
        <contrib contrib-type="author">
          <string-name>Mariona Taulé</string-name>
          <xref ref-type="aff" rid="aff2">2</xref>
          <xref ref-type="aff" rid="aff4">4</xref>
        </contrib>
        <aff id="aff0">
          <label>0</label>
          <institution>IIPAL</institution>
          ,
          <addr-line>CNRS-NUS-ASTAR</addr-line>
          ,
          <country country="SG">Singapore</country>
        </aff>
        <aff id="aff1">
          <label>1</label>
          <institution>IRIT, Université de Toulouse</institution>
          ,
          <addr-line>CNRS, Toulouse INP, UT3, Toulouse</addr-line>
          ,
          <country country="FR">France</country>
        </aff>
        <aff id="aff2">
          <label>2</label>
          <institution>SEPLN-CEDI2024: Seminar of the Spanish Society for Natural Language Processing at the 7th Spanish Conference on Informatics</institution>
        </aff>
        <aff id="aff3">
          <label>3</label>
          <institution>Uninettuno Telematic International University</institution>
          ,
          <addr-line>Corso Vittorio Emanuele II, Roma</addr-line>
          ,
          <country country="IT">Italy</country>
        </aff>
        <aff id="aff4">
          <label>4</label>
          <institution>Universitat de Barcelona - CLiC</institution>
          ,
          <addr-line>Gran Via de Les Corts Catalanes 585, Barcelona</addr-line>
          ,
          <country country="ES">Spain</country>
        </aff>
        <aff id="aff5">
          <label>5</label>
          <institution>University of Bari 'Aldo Moro'</institution>
          ,
          <addr-line>Via Crisanzio 42, Bari</addr-line>
          ,
          <country country="IT">Italy</country>
        </aff>
        <aff id="aff6">
          <label>6</label>
          <institution>University of Turin</institution>
          ,
          <addr-line>Corso Svizzera 185, Torino</addr-line>
          ,
          <country country="IT">Italy</country>
        </aff>
      </contrib-group>
      <abstract>
        <p>One of the Challenges for Europe should be to understand how media and fake news can reinforce prejudices against immigrants. The main objective of the STERHEOTYPES (STudying European Racial Hoaxes and sterEOTYPES) project, led by the 'Aldo Moro' University of Bari and funded by the Fondazione Compagnia di San Paolo ("Challenges for Europe"), is to promote awareness of the psychological processes generated by racial hoaxes, in the new digital generations, in three European Mediterranean countries: Italy, Spain and France. This paper presents the main findings aimed at (i) Understanding and countering factors associated to online racial hoaxes and online stereotypes through psycho-educational interventions in schools using an ad hoc designed web-app; and (ii) Investigating the features and dynamics of racist stereotypes through computational analysis based on novel annotated datasets that have been used to train automatic stereotype detection models in multilingual and multicultural perspectives.</p>
      </abstract>
      <kwd-group>
        <kwd>eol&gt;Racial misinformation</kwd>
        <kwd>Stereotypes detection</kwd>
        <kwd>Multilingual annotated corpora</kwd>
        <kwd>Implicitness</kwd>
        <kwd>SocioPsychological models 1</kwd>
      </kwd-group>
    </article-meta>
  </front>
  <body>
    <sec id="sec-1">
      <title>1. Introduction</title>
      <p>The international Project STERHEOTYPES
(https://www.irit.fr/sterheotypes) starts from the
consideration that one of the main Challenges to be
addressed in European countries should be to
understand and promote awareness on how media
and fake news can reinforce prejudices against
refugees and immigrants, especially in the
Mediterranean area. In this context the levels of
prejudice of ‘common people’ could increase when fed
by ‘fake’ information, as in the case of so-called ‘racial</p>
      <p>0000-0002-8957-665X (F. D’Errico); 0000-0002-8857-4484 (C.
Bosco); 0000-0002-9023-0656 (M. Paciello); 0000-0002-0685-1864
(F. Benamara); 0000-0001-5002-4834 (P. G. Cicirelli)
0000-00015991-370X (V. Patti); 0000-0001-9641-0714 (V. Moriceau);
00000003-0089-940X (M. Taulé)
© 2023 Copyright for this paper by its authors. The use permitted under
Creative Commons License Attribution 4.0 International (CC BY 4.0).</p>
      <p>
        CEUR Workshop Proceedings (CEUR-WS.org)
hoaxes’ [
        <xref ref-type="bibr" rid="ref1">1</xref>
        ]. Racial Hoaxes (RHs) are communicative
acts created to spread information regarding alleged
threats to someone’s health or safety by individuals or
groups because of race, ethnicity or religion. In relation
to RHs, the literature has considered people’s
shortterm emotional reactions while neglecting
sociopsychological processes [
        <xref ref-type="bibr" rid="ref2">2</xref>
        ], such as stereotypes and
prejudices, which can reinforce anti-immigrants’
attitudes [
        <xref ref-type="bibr" rid="ref3">3</xref>
        ] especially considering their impact on
young ‘digital natives’. In this sense, the project seeks
to promote, first of all, civic awareness for future
European citizens by contributing to the development
of their social resilience to pervasive disinformation
on immigration by fostering their prosocial attitude
and sense of solidarity by means of a cross-cultural
approach. Therefore, the main aim of the
STERHEOTYPES project, is to investigate the
stereotypes against immigrants, to promote
awareness related to the psychological processes
generated by racial hoaxes, particularly, in new digital
generations, by means of integrated methodological
approaches coming from psychology and
computational linguistics, observing the multilingual
and multicultural scenario in three European
Mediterranean countries: Italy, Spain and France. In
particular, the psychological teams, University of Bari
(UniBari) and Uninettuno University (Utiu),
performed experimental studies in real educational
contexts with the aim of understanding the
sociopsychological processes arising from online RHs by
considering individual differences related to prejudice
and their potential effects on emotional and
selfregulative processes within online communicative
contexts. The three computational linguistics teams
involved in the project, Università di Torino (UniTo),
Universitat de Barcelona (UniBa) and Université du
Toulouse (UniTou), worked instead on the
development of linguistic resources and tools for the
automatic detection of stereotypes. In particular, the
three groups defined a common methodology for the
collection and a shared scheme for the fine-grained
annotation of the collected data, inspired by
psychological studies (mainly Stereotype Content
Model [
        <xref ref-type="bibr" rid="ref4">4</xref>
        ]). Using this methodology and applying the
schema, they created a series of comparable corpora
that enabled computational experiments in a
multilingual environment, but also linguistic analyses.
The main research questions the STERHEOTYPES
project would like to address are the following:
- RQ1: What are the psychological features
(values, self-efficacy, analytical reasoning, prejudice)
that make young people more easily influenced by
racial hoaxes?
- RQ2: Can an ad hoc intervention lead to
adolescents becoming aware of media biases and
proactive in promoting intergroup contact?
- RQ3: What are the linguistic patterns that
emerged from the expressions of ethnic stereotypes in
the different languages studied?
- RQ4: Is it possible to automatically detect
stereotypes?
      </p>
    </sec>
    <sec id="sec-2">
      <title>2. Scientific and Technical results</title>
      <sec id="sec-2-1">
        <title>2.1. Theoretical framework and definition of cases and tools</title>
        <p>The project (led by UniBari) started with literature
review on RHs aimed at selecting and classifying
several types of RHs according to their focus on the
main different actors involved in hosting immigrants
that can negatively influence attitudes. UniBari
contributed to consolidating the project’s
psycholinguistic framework in relation to the potential
linguistic features to take into account, such as
cognitive stereotypes, prejudices, stance, emotional
responses and attitudes toward immigrants (RQ1).
This led UniTo and UniBari to release a first guidelines
for the annotation of stereotypes to be applied to
multilingual corpora extracted from social media.
Meanwhile, Utiu focused on the definition of
psychological variables and evaluation tools to be used
for the experimental part of the project, in order to
understand the role of individual differences in
moderating media effects on adolescents’ responses
and in maintaining or in changing anti-immigrants’
attitudes/stances (RQ2).</p>
      </sec>
      <sec id="sec-2-2">
        <title>2.2. Data and corpus collection and Analysis</title>
        <p>To analyze and understand the stereotypes,
prejudices and emotional reactions generated by RHs
in a cross-cultural perspective (RQ3), and to identify
the way in which these stereotypes are linguistically
expressed and to be able to detect them automatically
(RQ4), the following corpora were created:</p>
        <p>
          - The RacialHoax corpus consists of 239 RHs (70 in
French, 97 in Italian and 72 in Spanish) related to
immigration which were manually extracted from
French, Italian and Spanish fact-checking websites or
newspaper articles verifying or refuting claims made
in social media. Then, we used the items in these
corpora as seeds for collecting conversations, which
were reactions to these hoaxes, retrieved from Twitter
to create the StereoHoax corpus [
          <xref ref-type="bibr" rid="ref5">5</xref>
          ]. Regarding the
annotation of the RacialHoax corpus, we manually
classified each RH into six categories in accordance
with the main topic they addressed (‘Benefits’,
‘Security’, ‘Migration control’, ‘Culture/Religion’,
‘Public Health’ and ‘Others’). We also annotated other
categories such as the Target of the RH, Stance,
Implicitness (i.e. whether the stereotype was
expressed implicitly or explicitly), the event described,
and for each of these categories the words associated
to them that are crucial for classifying these categories.
D’Errico and colleagues [
          <xref ref-type="bibr" rid="ref1">1</xref>
          ] considered these initial
categories and, in addition, the annotation of further
psycholinguistic features (such as whether the
immigrants are described as the subject or object of
the RH, the verbal form, types of adjectives and the
presence of affective words) to conduct a deeper
psycholinguistic analysis of the Italian RHs.
        </p>
        <p>
          The StereoHoax corpus consists of 17,814 tweets
(9,342 in French, 3,123 in Italian and 5,349 in Spanish)
reporting on and responding to racial or ethnic hoaxes
about immigrants dated from 2019 to 2022. This
corpus was also manually annotated with the presence
or absence of ‘Stereotype’, ‘Contextuality’ (to indicate
whether the conversational context is needed to
interpret the stereotype), ‘Implicitness’ (explicit or
implicit stereotype) and the forms of ‘Discredit’
described in Bosco and colleagues [
          <xref ref-type="bibr" rid="ref6">6</xref>
          ] (benevolence,
dominance up, affective competence, dominance
down, competence and physical based on the Fiske’s
Stereotype Content Model [
          <xref ref-type="bibr" rid="ref4 ref7">4, 7</xref>
          ], The Spanish part of
StereoHoax was also annotated with the ‘Types of
implicitness’ following the proposal described in
Schmeisser and colleagues [
          <xref ref-type="bibr" rid="ref8">8</xref>
          ] and the ‘Stereotype
category’ applied in the DETESTS dataset [
          <xref ref-type="bibr" rid="ref9">9</xref>
          ]. The
Italian subset was also annotated with the ‘Stance’
expressed in the messages of the conversations
towards the veracity of the hoax [
          <xref ref-type="bibr" rid="ref10">10</xref>
          ] adopting the
SDQC schema [
          <xref ref-type="bibr" rid="ref11">11</xref>
          ] for indicating whether the author of
the message ‘Support’, ‘Deny’, ‘Query’ or ‘Comment’
the veracity of the hoax, and adding the label ‘Head’ to
identify the texts that spread the hoax or start the
conversational thread. The Italian part of StereoHoax
is also being annotated with ‘Type of implicitness’.
Finally, for the French part, in addition to annotating
for the presence/absence of stereotypes and stance as
well as types of discredit, we also annotated for the
presence/absence of hate speech. This will be
particularly useful for multitask learning experiments,
where hate speech can help for stereotype detection
and vice-versa (see Chiril and colleagues [
          <xref ref-type="bibr" rid="ref12">12</xref>
          ]).
        </p>
        <p>
          The aim of these corpora is twofold: 1) to analyse
the way in which stereotypes are expressed in the
languages studied and 2) to be used as datasets for
training and evaluating systems based on machine
learning models for detecting and classifying
stereotypes. Several experiments were performed
using these corpora. For instance, in Bourgeade and
colleagues [
          <xref ref-type="bibr" rid="ref5">5</xref>
          ], a first cross-lingual comparative
analysis of StereoHoax was presented, focusing on the
interaction between the topics of RHs, stereotypes and
the forms of discredit expressed in the messages of
StereoHoax in French, Italian and Spanish. Cignarella
and colleagues [
          <xref ref-type="bibr" rid="ref10">10</xref>
          ] analyse the distribution of stance
labels and their interrelationship with stereotypes
providing information about the way in which the
structure and nature of conversations and lexical
choices in messages may affect the perceived stance of
the user to RHs. Schmeisser-Nieto and colleagues [
          <xref ref-type="bibr" rid="ref13">13</xref>
          ]
describes BERT-based models designed to detect
stereotypes related to immigrants trained with the
Spanish subset of the StereoHoax corpus. Predictions
from GPT-4 are also generated and analised. The aim
is to provide insight into linguistic distinctions in the
way humans and these models perceive stereotypes.
The results obtained show the need to refer to the
conversational context to interpret the stereotype and
the difficulty to identify implicit stereotypes,
particularly, for models. The StereoHoax corpus in
Spanish will be used in the DETESTS-Dis task at
IberLEF 2024 (https://detests-dis.github.io/).
        </p>
      </sec>
      <sec id="sec-2-3">
        <title>2.3. Experimental psychological studies in natural settings</title>
        <p>
          The psychological units collected a sample of real
data produced by adolescents by contacting Italian
schools and performing a data analysis aimed at the
definition of individual psychological dimensions
(personal values, empathy levels, anti-immigrant
attitude and implicit prejudice) that could moderate
the responses of young people to RHs. We also
collected spontaneous comments by the adolescents
reflecting their reaction to stimuli on emotions and
attitudes to RHs about immigrants. In a first step,
UniBari and Utiu collected data by involving more than
2600 students mainly adolescents by means of focus
groups to test their knowledge about RHs and fake
news. Then, they tested measures and RHs that can
affect digital natives’ stereotypes and also their
emotions in Italian contexts (Rome, Bari). Finally, they
engaged with a web-app called ‘ROLLING MINDS!’ [
          <xref ref-type="bibr" rid="ref14">14</xref>
          ]
which is aimed at testing adolescents’ comments and
reactions to RHs and misleading news. In cooperation
with the computational linguists at UniTo, the
psychological units developed an intervention
procedure focused on so-called media biases [
          <xref ref-type="bibr" rid="ref15">15</xref>
          ].
More than 600 Italian students were involved, first in
a simulated version and then by means of a
conversational approach to recognize linguistic
stereotypes and anti-immigrant narratives. The
conversational web-app ROLLING MINDS!’ will be
translated in Spanish and English in collaboration with
UniBa to collect longitudinal and cross-cultural data.
The Italian data collected across several studies was
also analysed in relation to students’ data to propose a
first definition of the socio-psychological processes
underlying influence of RHs [
          <xref ref-type="bibr" rid="ref16 ref17 ref18 ref19">16, 17, 18, 19</xref>
          ].
        </p>
      </sec>
      <sec id="sec-2-4">
        <title>2.4. Action research for promotion</title>
        <p>
          of awareness on racial hoaxes’
Both experimental and media findings were
presented by UniBari and Utiu in schools to promote
‘digital natives’ awareness of the toxicity of RH [
          <xref ref-type="bibr" rid="ref14 ref20">14,
20</xref>
          ]. In particular, young people were invited to reflect
on the emotional and cognitive processes involved in
the discussion of RHs considering the source of
messages, their media biases and immigrants’ points
of view [
          <xref ref-type="bibr" rid="ref15">15</xref>
          ]. Teachers and students were involved in
several debriefings in which the researcher explained
the theoretical framework guiding research and the
psychological differences that could interact with
mediated contexts. The researchers and other scholars
in the field of misinformation, hate speech and online
racism will also provide a video-course and
comprehensive guidelines to the individuals involved
and future teachers for promoting the diffusion of a
preventive intervention by using the ROLLING-MINDS!
web-app (Figures 1, 2) to promote self-reflection on
personal aspects involved in the discussion of RHs.
This video-course will be available on the project
website at the end of the project. Finally, the web-app,
thanks to an agreement with BDS design (which
supported psychological units in the implementation
of the web-app), will be used to monitor the trends of
the psychosocial variables related to RHs throughout
and after the end of the STERHEOTYPES project.
        </p>
      </sec>
      <sec id="sec-2-5">
        <title>2.5. Science communication measures</title>
        <p>All the meetings and scientific communications
across reciprocal domains were fully documented at
the project website, where both researchers and
schools involved in the experimental part and other
possible stakeholders (teachers, journalists,
policymakers) can deepen these topics.
https://www.irit.fr/sterheotypes/publications. As to
the performed synergies, the project team was
composed by senior scholars, all females, skilled in
Psychology and Computational Linguistics. They
involved, thanks to the project, 10 among pre and
postdoc junior researchers under their supervision; They,
at different stages of their academic career were
supported by the Project, in particular dr Cignarella
and Frenda from UniTorino, dr. Corbelli from
UniNettuno, Sebastian Wolfgang Schmeisser
UniBarcelona, Paolo Giovanni Cicirelli and Carmela
Sportelli from UniBari, Tom Bourgade from
UniToulose will discuss their PhD Thesis on the project
theme, by disseminating their results across academic
communities coming from Psychology and
Computational linguistics.</p>
      </sec>
    </sec>
    <sec id="sec-3">
      <title>3. Conclusions</title>
      <p>
        Regarding the psychological RQ1, we showed across
studies that promoting an analytical and self-regulated
approach to the reading of RHs led adolescents to be
more aware and prone to intergroup contact. These
considerations are based on results emerging from
several sessions with the conversational web-app
‘ROLLING MINDS!’ [
        <xref ref-type="bibr" rid="ref14 ref20">14, 20</xref>
        ]. The remaining months at
the end of the project will take advantage of the
experience gained in these three years to, in the case of
the psychological units, collect data and reactions to
RHs by adolescents, in order to allow the working
group of computational linguists to carry out a
detection of stereotypes in a natural context, making a
comparison between detection in social media and in
real contexts, by also taking into account
sociopsychological variables.
      </p>
      <p>
        This effort allows us to create a new dataset named
STERHEOSCHOOL (currently under review) that will
be presented in future European congresses on these
themes. Finally, the implementation of the web-app
has demonstrated good results in terms of prejudice
prevention [
        <xref ref-type="bibr" rid="ref14 ref20">14, 20</xref>
        ], and has undergone some
variations which will be further tested in Italian
schools. Furthermore, the translation by the UniBa will
allow the web-app to be applied in other contexts
(Spanish and English in particular). The results of the
subsequent surveys will allow us to further
understand the risk and protective factors of racial
misinformation in adolescence. The outcomes of the
project allow us to pave the way for further
investigations in the area of stereotype detection.
Regarding resources (RQ3), we are working on the
development of a novel corpus annotated with the
same scheme applied to the StereoHoax corpus, but
including texts collected in the experiments organized
by the team of psychologists in schools, which
represent a genre that is different but characterized by
an important similarity, particularly the collection
with a conversational context. The availability of
comparable multilingual corpora is currently enabling
the application of data augmentation techniques based
on an approach that includes machine translation and
back translation. This will help us to address the
limited size of the currently existing data sets for the
three languages of the project. Regarding the
development of tools for stereotype detection (RQ4),
we are continuing our research on modeling this
complex phenomenon whose detection can be
especially challenging.
      </p>
    </sec>
    <sec id="sec-4">
      <title>Acknowledgements</title>
      <p>This work was supported by the European project
‘STERHEOTYPES—STudyingEuropean Racial Hoaxes
and sterEOTYPES’ funded by ‘Challenge for Europe’
call for Project, Fondazione Compagnia di San Paolo
and the Volkswagen Stiftung (CUP:
B99C20000640007). We extend our gratitude to the
BSD Design team for their technical assistance and
support in the development of the web app "Rolling
Minds".</p>
    </sec>
  </body>
  <back>
    <ref-list>
      <ref id="ref1">
        <mixed-citation>
          [1]
          <string-name>
            <surname>F. D'Errico</surname>
            ,
            <given-names>C.</given-names>
          </string-name>
          <string-name>
            <surname>Papapicco</surname>
          </string-name>
          , M. Taulé, 'Immigrants, Hell on Board'.
          <article-title>Stereotypes and Prejudice Emerging from Racial Hoaxes through a PsychoLinguistic Analysis</article-title>
          ,
          <source>Journal of Language and Discrimination</source>
          ,
          <volume>6</volume>
          (
          <issue>2</issue>
          ) (
          <year>2022</year>
          ):
          <fpage>191</fpage>
          -
          <lpage>212</lpage>
          .
        </mixed-citation>
      </ref>
      <ref id="ref2">
        <mixed-citation>
          [2]
          <string-name>
            <surname>F. D'Errico</surname>
            ,
            <given-names>M.</given-names>
          </string-name>
          <string-name>
            <surname>Paciello</surname>
          </string-name>
          ,
          <article-title>Online moral disengagement and hostile emotions in discussions on hosting immigrants</article-title>
          ,
          <source>Internet Research</source>
          ,
          <volume>28</volume>
          (
          <issue>5</issue>
          ) (
          <year>2018</year>
          ):
          <fpage>1313</fpage>
          -
          <lpage>1335</lpage>
          .
        </mixed-citation>
      </ref>
      <ref id="ref3">
        <mixed-citation>
          [3]
          <string-name>
            <given-names>C.</given-names>
            <surname>Wright</surname>
          </string-name>
          ,
          <string-name>
            <given-names>R.</given-names>
            <surname>Brinklow-Vaughn</surname>
          </string-name>
          ,
          <string-name>
            <given-names>K.</given-names>
            <surname>Johannes</surname>
          </string-name>
          ,
          <string-name>
            <given-names>F.</given-names>
            <surname>Rodriguez</surname>
          </string-name>
          , (
          <year>2021</year>
          ).
          <article-title>Media Portrayals of Immigration and Refugees in Hard and Fake News and Their Impact on Consumer Attitudes</article-title>
          ,
          <source>Howard Journal of Communications</source>
          ,
          <volume>32</volume>
          (
          <issue>4</issue>
          ) (
          <year>2021</year>
          ):
          <fpage>331</fpage>
          -
          <lpage>351</lpage>
          .
        </mixed-citation>
      </ref>
      <ref id="ref4">
        <mixed-citation>
          [4]
          <string-name>
            <given-names>S. T.</given-names>
            <surname>Fiske</surname>
          </string-name>
          ,
          <string-name>
            <given-names>A. J. C.</given-names>
            <surname>Cuddy</surname>
          </string-name>
          ,
          <string-name>
            <given-names>P.</given-names>
            <surname>Glick</surname>
          </string-name>
          ,
          <string-name>
            <given-names>J.</given-names>
            <surname>Xu</surname>
          </string-name>
          ,
          <article-title>A model of (often mixed) stereotype content: Competence and warmth respectively follow from perceived status and competition</article-title>
          .
          <source>Journal of Personality and Social Psychology</source>
          ,
          <volume>82</volume>
          (
          <issue>6</issue>
          ), (
          <year>2002</year>
          ):
          <fpage>878</fpage>
          -
          <lpage>902</lpage>
          .
        </mixed-citation>
      </ref>
      <ref id="ref5">
        <mixed-citation>
          [5]
          <string-name>
            <given-names>T.</given-names>
            <surname>Bourgeade</surname>
          </string-name>
          ,
          <string-name>
            <given-names>A.T.</given-names>
            <surname>Cignarella</surname>
          </string-name>
          ,
          <string-name>
            <given-names>S.</given-names>
            <surname>Frenda</surname>
          </string-name>
          ,
          <string-name>
            <given-names>M.</given-names>
            <surname>Laurent</surname>
          </string-name>
          ,
          <string-name>
            <given-names>W.S.</given-names>
            <surname>Schmeisser-Nieto</surname>
          </string-name>
          ,
          <string-name>
            <given-names>F.</given-names>
            <surname>Benamara</surname>
          </string-name>
          ,
          <string-name>
            <given-names>C.</given-names>
            <surname>Bosco</surname>
          </string-name>
          ,
          <string-name>
            <given-names>V.</given-names>
            <surname>Moriceau</surname>
          </string-name>
          ,
          <string-name>
            <given-names>V.</given-names>
            <surname>Patti</surname>
          </string-name>
          ,
          <string-name>
            <given-names>M.</given-names>
            <surname>Taulé</surname>
          </string-name>
          ,
          <article-title>A Multilingual Dataset of Racial Stereotypes in Social Media Conversational Threads, in: Findings of the Association for Computational Linguistics</article-title>
          ,
          <string-name>
            <surname>EACL</surname>
          </string-name>
          <year>2023</year>
          ,
          <year>2023</year>
          , Croatia, pp.
          <fpage>674</fpage>
          -
          <lpage>684</lpage>
          . doi:
          <volume>10</volume>
          .18653/v1/
          <year>2023</year>
          .findings-eacl.
          <fpage>51</fpage>
        </mixed-citation>
      </ref>
      <ref id="ref6">
        <mixed-citation>
          [6]
          <string-name>
            <given-names>C.</given-names>
            <surname>Bosco</surname>
          </string-name>
          ,
          <string-name>
            <given-names>V.</given-names>
            <surname>Patti</surname>
          </string-name>
          ,
          <string-name>
            <given-names>S.</given-names>
            <surname>Frenda</surname>
          </string-name>
          ,
          <string-name>
            <given-names>A.T.</given-names>
            <surname>Cignarella</surname>
          </string-name>
          ,
          <string-name>
            <given-names>M.</given-names>
            <surname>Paciello</surname>
          </string-name>
          ,
          <string-name>
            <surname>F.</surname>
          </string-name>
          <article-title>D'Errico, Detecting Racial Stereotypes: An Italian Social Media Corpus where Psychology Meets NLP</article-title>
          ,
          <source>Information Processing and Management</source>
          ,
          <volume>60</volume>
          (
          <issue>1</issue>
          ) (
          <year>2023</year>
          ):
          <fpage>103118</fpage>
          .
        </mixed-citation>
      </ref>
      <ref id="ref7">
        <mixed-citation>
          [7]
          <string-name>
            <surname>F. D'Errico</surname>
            ,
            <given-names>I. Poggi</given-names>
          </string-name>
          , L. Vincze,
          <article-title>Discrediting signals. A model of social evaluation to study discrediting moves in political debates</article-title>
          ,
          <source>Journal on Multimodal User Interfaces</source>
          ,
          <volume>6</volume>
          (
          <year>2012</year>
          ):
          <fpage>163</fpage>
          -
          <lpage>178</lpage>
          .
        </mixed-citation>
      </ref>
      <ref id="ref8">
        <mixed-citation>
          [8]
          <string-name>
            <given-names>W.S.</given-names>
            <surname>Schmeisser-Nieto</surname>
          </string-name>
          ,
          <string-name>
            <given-names>M.</given-names>
            <surname>Nofre</surname>
          </string-name>
          ,
          <string-name>
            <given-names>M.</given-names>
            <surname>Taulé</surname>
          </string-name>
          ,
          <article-title>Criteria for the Annotation of Implicit Stereotypes</article-title>
          ,
          <source>in: Proceedings of the 13th Conference on Language Resources and Evaluation</source>
          ,
          <string-name>
            <surname>LREC</surname>
          </string-name>
          <year>2022</year>
          , Marseille,
          <year>2022</year>
          , pp.
          <fpage>753</fpage>
          -
          <lpage>762</lpage>
          .
        </mixed-citation>
      </ref>
      <ref id="ref9">
        <mixed-citation>
          [9]
          <string-name>
            <given-names>A.</given-names>
            <surname>Ariza-Casabona</surname>
          </string-name>
          ,
          <string-name>
            <given-names>W.S.</given-names>
            <surname>Schmeisser-Nieto</surname>
          </string-name>
          ,
          <string-name>
            <given-names>M.</given-names>
            <surname>Nofre</surname>
          </string-name>
          ,
          <string-name>
            <given-names>M.</given-names>
            <surname>Taulé</surname>
          </string-name>
          ,
          <string-name>
            <given-names>E.</given-names>
            <surname>Amigó</surname>
          </string-name>
          ,
          <string-name>
            <given-names>B.</given-names>
            <surname>Chulvi</surname>
          </string-name>
          ,
          <string-name>
            <given-names>P.</given-names>
            <surname>Rosso</surname>
          </string-name>
          ,
          <article-title>Overview of the DETESTS at IberLEF 2022: DETEction and classification of racial STereotypes in Spanish</article-title>
          ,
          <source>Procesamiento del Lenguaje Natural</source>
          ,
          <volume>69</volume>
          (
          <year>2022</year>
          ):
          <fpage>217</fpage>
          -
          <lpage>228</lpage>
          .
        </mixed-citation>
      </ref>
      <ref id="ref10">
        <mixed-citation>
          [10]
          <string-name>
            <given-names>A.T.</given-names>
            <surname>Cignarella</surname>
          </string-name>
          ,
          <string-name>
            <given-names>S.</given-names>
            <surname>Frenda</surname>
          </string-name>
          ,
          <string-name>
            <given-names>T.</given-names>
            <surname>Bourgeade</surname>
          </string-name>
          ,
          <string-name>
            <given-names>C.</given-names>
            <surname>Bosco</surname>
          </string-name>
          ,
          <string-name>
            <surname>F.</surname>
          </string-name>
          <article-title>D'Errico, Linking Stance and Stereotypes About Migrants in Italian Fake News</article-title>
          ,
          <source>in: Proceedings of CLiC-it 2023 19th Italian Conference on Computational Linguistics</source>
          , CEUR Ws-org Vol-
          <volume>3596</volume>
          , Venice, Italy,
          <year>2023</year>
          .
        </mixed-citation>
      </ref>
      <ref id="ref11">
        <mixed-citation>
          [11]
          <string-name>
            <given-names>A.</given-names>
            <surname>Aker</surname>
          </string-name>
          ,
          <string-name>
            <given-names>L.</given-names>
            <surname>Derczynski</surname>
          </string-name>
          ,
          <string-name>
            <given-names>K.</given-names>
            <surname>Bontcheva</surname>
          </string-name>
          ,
          <article-title>Simple Open Stance Classification for Rumour Analysis</article-title>
          ,
          <source>in: Proceedings of the International Conference Recent Advances in Natural Language Processing (RANLP</source>
          <year>2017</year>
          ), INCOMA Ltd.,
          <year>2017</year>
          .
        </mixed-citation>
      </ref>
      <ref id="ref12">
        <mixed-citation>
          [12]
          <string-name>
            <given-names>P.</given-names>
            <surname>Chiril</surname>
          </string-name>
          ,
          <string-name>
            <given-names>F.</given-names>
            <surname>Benamara</surname>
          </string-name>
          ,
          <string-name>
            <given-names>V.</given-names>
            <surname>Moriceau</surname>
          </string-name>
          , “
          <article-title>be nice to your wife! the restaurants are closed”: Can gender stereotype detection improve sexism classification?</article-title>
          .
          <source>In: Findings of the Association for Computational Linguistics: EMNLP</source>
          <year>2021</year>
          (pp.
          <fpage>2833</fpage>
          -
          <lpage>2844</lpage>
          ).
        </mixed-citation>
      </ref>
      <ref id="ref13">
        <mixed-citation>
          [13]
          <string-name>
            <given-names>W.S</given-names>
            <surname>Schmeisser-Nieto</surname>
          </string-name>
          ,
          <article-title>Human vs</article-title>
          .
          <source>Machine Perceptions on Immigration Stereotypes, in: Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation</source>
          ,
          <string-name>
            <surname>LRECCOLING</surname>
          </string-name>
          <year>2024</year>
          , Torino,
          <year>2024</year>
          .
        </mixed-citation>
      </ref>
      <ref id="ref14">
        <mixed-citation>
          [14]
          <string-name>
            <surname>F. D'Errico</surname>
            ,
            <given-names>P.G.</given-names>
          </string-name>
          <string-name>
            <surname>Cicirelli</surname>
            , G. Gorbelli,
            <given-names>M.</given-names>
          </string-name>
          <string-name>
            <surname>Paciello</surname>
          </string-name>
          (
          <year>2024</year>
          )
          <article-title>Rolling Minds. a Conversational Media to Promote Intergroup Contact by Countering Racial Misinformation Through Socio-Analytic Processing in Adolescence.</article-title>
        </mixed-citation>
      </ref>
      <ref id="ref15">
        <mixed-citation>
          [15]
          <string-name>
            <given-names>R.</given-names>
            <surname>Paul</surname>
          </string-name>
          , L. Elder,
          <article-title>The thinkers guide for conscientious citizens on how to detect media bias and propaganda in national and world news: Based on critical thinking concepts and tools</article-title>
          .
          <source>Rowman &amp; Littlefield</source>
          ,
          <year>2004</year>
          .
        </mixed-citation>
      </ref>
      <ref id="ref16">
        <mixed-citation>
          [16]
          <string-name>
            <surname>F. D'Errico</surname>
            ,
            <given-names>G.</given-names>
          </string-name>
          <string-name>
            <surname>Corbelli</surname>
            ,
            <given-names>C.</given-names>
          </string-name>
          <string-name>
            <surname>Papapicco</surname>
            ,
            <given-names>M.</given-names>
          </string-name>
          <string-name>
            <surname>Paciello</surname>
          </string-name>
          ,
          <article-title>How Personal Values Count in Misleading News Sharing with Moral Content</article-title>
          ,
          <source>Behavioral Sciences</source>
          ,
          <volume>12</volume>
          (
          <issue>9</issue>
          ) (
          <year>2022</year>
          ),
          <volume>302</volume>
          . doi:
          <volume>10</volume>
          .3390/bs12090302
        </mixed-citation>
      </ref>
      <ref id="ref17">
        <mixed-citation>
          [17]
          <string-name>
            <given-names>G.</given-names>
            <surname>Corbelli</surname>
          </string-name>
          ,
          <string-name>
            <given-names>P.G.</given-names>
            <surname>Cicirelli</surname>
          </string-name>
          ,
          <string-name>
            <surname>F. D'Errico</surname>
            ,
            <given-names>M.</given-names>
          </string-name>
          <string-name>
            <surname>Paciello</surname>
          </string-name>
          ,
          <article-title>Preventing Prejudice Emerging from Misleading News among Adolescents: The Role of Implicit Activation and Regulatory Self-Efficacy in Dealing with Online Misinformation</article-title>
          ,
          <source>Social Sciences</source>
          ,
          <volume>12</volume>
          (
          <issue>9</issue>
          ) (
          <year>2023</year>
          ):
          <fpage>470</fpage>
          .
        </mixed-citation>
      </ref>
      <ref id="ref18">
        <mixed-citation>
          [18]
          <string-name>
            <given-names>C.</given-names>
            <surname>Papapicco</surname>
          </string-name>
          ,
          <string-name>
            <given-names>I.</given-names>
            <surname>Lamanna</surname>
          </string-name>
          ,
          <string-name>
            <surname>F.</surname>
          </string-name>
          <article-title>D'Errico, 'Adolescents' vulnerability to False Information and to Racial Hoaxes. A qualitative content analysis on Italian sample</article-title>
          ,
          <source>Multimodal Technologies and Interaction</source>
          ,
          <volume>6</volume>
          (
          <issue>3</issue>
          ) (
          <year>2022</year>
          ):
          <fpage>20</fpage>
          . doi:
          <volume>10</volume>
          .3390/mti6030020
        </mixed-citation>
      </ref>
      <ref id="ref19">
        <mixed-citation>
          [19]
          <string-name>
            <given-names>M.</given-names>
            <surname>Paciello</surname>
          </string-name>
          ,
          <string-name>
            <given-names>G.</given-names>
            <surname>Corbelli</surname>
          </string-name>
          ,
          <string-name>
            <surname>F.</surname>
          </string-name>
          <article-title>D'Errico, The Role of Self-efficacy Beliefs in Dealing with Misinformation among Adolescents, Frontiers in Media Psychology</article-title>
          , vol.
          <volume>14</volume>
          , (
          <year>2023</year>
          ).
        </mixed-citation>
      </ref>
      <ref id="ref20">
        <mixed-citation>
          [20]
          <string-name>
            <surname>F.D'Errico</surname>
            ,
            <given-names>P.G.</given-names>
          </string-name>
          <string-name>
            <surname>Cicirelli</surname>
            , G. Corbelli,
            <given-names>M.</given-names>
          </string-name>
          <string-name>
            <surname>Paciello</surname>
          </string-name>
          ,
          <article-title>Addressing racial misinformation at school: a psycho-social intervention aimed at reducing ethnic moral disengagement in adolescents, Social Psychology of Education, (</article-title>
          <year>2023</year>
          ). doi:
          <volume>10</volume>
          .1007/s11218-023-09777-z
        </mixed-citation>
      </ref>
    </ref-list>
  </back>
</article>