Horizon Europe · Horizon Europe (HORIZON)
Advisory support and network for countering and preventing radicalisation, extremism, hate speech and polarisation
Call summary
From the official text, opening part
Expected Outcome: Projects should contribute to all of the following expected outcomes: Political, societal, educational stakeholders, and researchers have an improved understanding of theoretical models and provided pathways for implementing solutions to combat extremism, radicalisation, hate speech and polarisation. Public authorities, law enforcement agencies, local authorities, NGOs, and community actors are more engaged in implementing and adapting solutions addressing radicalisation, extremism, hate speech, and polarisation in their respective contexts. EU institutions, national policymakers and judicial bodies can draw on an enhanced evidence-base for their decision-making through scientific, political, and legal assessments of research results in real-life contexts, enabling replication of methods, legislative changes, and innovation. Improved understanding of the root causes of … more
Human sciences, including research and studiesPolitical scienceSocial NetworksSocial sciences, interdisciplinaryDemocratic valuesExtremismHate speechOnline hate ecosystemsPolarisationRacismRadicalisationSocial cohesionXenophobia
Academics who may be relevant
By subject fit
30-
%73NEVFEL BOZ
Shared topics: Hate Speech and Cyberbullying Detection
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%71DİLEK ÖZGE ERDEM
Shared topics: Hate Speech and Cyberbullying Detection
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%64YELİZ DEDE ÖZDEMİR
Shared topics: Hate Speech and Cyberbullying Detection
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%63AYBERK CAN ERTUNA
Shared topics: Terrorism, Counterterrorism, and Political Violence · Hate Speech and Cyberbullying Detection
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%63BÜŞRA KIZIK
Shared topics: Terrorism, Counterterrorism, and Political Violence · Hate Speech and Cyberbullying Detection
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%63TİRŞE ERBAYSAL FİLİBELİ
Shared topics: Hate Speech and Cyberbullying Detection
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%60ÖZLEM ÇELİK
Shared topics: Hate Speech and Cyberbullying Detection
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%59AHMET FARUK ÇEÇEN
Shared topics: Hate Speech and Cyberbullying Detection
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%57YAĞMUR ÇENBERLİ
Shared topics: Hate Speech and Cyberbullying Detection
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%56MERT MORALI
Shared topics: Hate Speech and Cyberbullying Detection
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%56PELİN CANBAY
Shared topics: Hate Speech and Cyberbullying Detection
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%55FURKAN SAİTOĞLU
Shared topics: Hate Speech and Cyberbullying Detection
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%55ÖMER TOPUZ
Shared topics: Hate Speech and Cyberbullying Detection
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%54MİHRİBAN ŞEVVAL TOPAL
Shared topics: Hate Speech and Cyberbullying Detection
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%54OZAN TOK
Shared topics: Hate Speech and Cyberbullying Detection
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%54RUHDAN UZUN
Shared topics: Hate Speech and Cyberbullying Detection
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%53MERVE GENÇYÜREK ERDOĞAN
Shared topics: Hate Speech and Cyberbullying Detection
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%52MERAL EKİCİ
Shared topics: Hate Speech and Cyberbullying Detection
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%52YEŞİM YILMAZ
Shared topics: Hate Speech and Cyberbullying Detection
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%51AYŞE DİLŞAD KESKİN
Shared topics: Hate Speech and Cyberbullying Detection
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%50AYŞE İREM SUNGAR
Shared topics: Hate Speech and Cyberbullying Detection
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%49KONUR ALP KOZ
Shared topics: Hate Speech and Cyberbullying Detection
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%49SEDA GÖKÇE TURAN
Shared topics: Hate Speech and Cyberbullying Detection
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%47CEREN ATİK
Shared topics: Hate Speech and Cyberbullying Detection
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%47HACI İBRAHİM DELİCE
Shared topics: Hate Speech and Cyberbullying Detection
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%46SÜMEYYE AYDIN BULUT
Shared topics: Hate Speech and Cyberbullying Detection
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%45GÖKÇE VAROL
Shared topics: Hate Speech and Cyberbullying Detection
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%42ABDURRAHMAN YAĞMUR TOPRAKLI
Research topics: Evacuation and Crowd Dynamics · Transportation Planning and Optimization · Cultural and Sociopolitical Studies
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%42HASAN BADEM
Shared topics: Voice and Speech Disorders
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%42VOLKAN ALTINTAŞ
Research topics: Sentiment Analysis and Opinion Mining · Misinformation and Its Impacts · Topic Modeling
The fit is computed by code on every request: semantic similarity (55%) between the call text (title, EU keywords, start of the official description) and the academic’s YÖKSİS fields, keywords and OpenAlex topics, plus shared distinctive terms (45%; common words weigh little). Below 40% is not shown. A subject hint only — not an eligibility, capacity or merit assessment. Hidden profiles are never listed.