Ufuk Avrupa · Horizon Europe (HORIZON)
Advisory support and network for countering and preventing radicalisation, extremism, hate speech and polarisation
Çağrı özeti
Resmi metinden, ilk bölüm
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 … devamı
Human sciences, including research and studiesPolitical scienceSocial NetworksSocial sciences, interdisciplinaryDemocratic valuesExtremismHate speechOnline hate ecosystemsPolarisationRacismRadicalisationSocial cohesionXenophobia
İlgili olabilecek akademisyenler
Konu uyumuna göre
30-
%73NEVFEL BOZ
Ortak konular: Hate Speech and Cyberbullying Detection
-
%71DİLEK ÖZGE ERDEM
Ortak konular: Hate Speech and Cyberbullying Detection
-
%64YELİZ DEDE ÖZDEMİR
Ortak konular: Hate Speech and Cyberbullying Detection
-
%63AYBERK CAN ERTUNA
Ortak konular: Terrorism, Counterterrorism, and Political Violence · Hate Speech and Cyberbullying Detection
-
%63BÜŞRA KIZIK
Ortak konular: Terrorism, Counterterrorism, and Political Violence · Hate Speech and Cyberbullying Detection
-
%63TİRŞE ERBAYSAL FİLİBELİ
Ortak konular: Hate Speech and Cyberbullying Detection
-
%60ÖZLEM ÇELİK
Ortak konular: Hate Speech and Cyberbullying Detection
-
%59AHMET FARUK ÇEÇEN
Ortak konular: Hate Speech and Cyberbullying Detection
-
%57YAĞMUR ÇENBERLİ
Ortak konular: Hate Speech and Cyberbullying Detection
-
%56MERT MORALI
Ortak konular: Hate Speech and Cyberbullying Detection
-
%56PELİN CANBAY
Ortak konular: Hate Speech and Cyberbullying Detection
-
%55FURKAN SAİTOĞLU
Ortak konular: Hate Speech and Cyberbullying Detection
-
%55ÖMER TOPUZ
Ortak konular: Hate Speech and Cyberbullying Detection
-
%54MİHRİBAN ŞEVVAL TOPAL
Ortak konular: Hate Speech and Cyberbullying Detection
-
%54OZAN TOK
Ortak konular: Hate Speech and Cyberbullying Detection
-
%54RUHDAN UZUN
Ortak konular: Hate Speech and Cyberbullying Detection
-
%53MERVE GENÇYÜREK ERDOĞAN
Ortak konular: Hate Speech and Cyberbullying Detection
-
%52MERAL EKİCİ
Ortak konular: Hate Speech and Cyberbullying Detection
-
%52YEŞİM YILMAZ
Ortak konular: Hate Speech and Cyberbullying Detection
-
%51AYŞE DİLŞAD KESKİN
Ortak konular: Hate Speech and Cyberbullying Detection
-
%50AYŞE İREM SUNGAR
Ortak konular: Hate Speech and Cyberbullying Detection
-
%49KONUR ALP KOZ
Ortak konular: Hate Speech and Cyberbullying Detection
-
%49SEDA GÖKÇE TURAN
Ortak konular: Hate Speech and Cyberbullying Detection
-
%47CEREN ATİK
Ortak konular: Hate Speech and Cyberbullying Detection
-
%47HACI İBRAHİM DELİCE
Ortak konular: Hate Speech and Cyberbullying Detection
-
%46SÜMEYYE AYDIN BULUT
Ortak konular: Hate Speech and Cyberbullying Detection
-
%45GÖKÇE VAROL
Ortak konular: Hate Speech and Cyberbullying Detection
-
%42ABDURRAHMAN YAĞMUR TOPRAKLI
Çalışma konuları: Evacuation and Crowd Dynamics · Transportation Planning and Optimization · Cultural and Sociopolitical Studies
-
%42HASAN BADEM
Ortak konular: Voice and Speech Disorders
-
%42VOLKAN ALTINTAŞ
Çalışma konuları: Sentiment Analysis and Opinion Mining · Misinformation and Its Impacts · Topic Modeling
Uyum oranı kodla, her istekte hesaplanır: çağrı metni (başlık, AB anahtar kelimeleri, resmi açıklamanın başı) ile akademisyenin YÖKSİS alanları, anahtar kelimeleri ve OpenAlex konuları arasındaki anlamsal yakınlık (%55) ve ortak ayırt edici terimler (%45; yaygın kelimeler düşük ağırlıklı). %40 altı gösterilmez. Bir konu önerisidir; başvuru uygunluğu, kapasite ya da başarı değerlendirmesi değildir. Gizli profiller listelenmez.