Shayan Alipour

ORCID: 0009-0004-7612-9043
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About
Contact & Profiles
Research Areas
  • Misinformation and Its Impacts
  • Complex Network Analysis Techniques
  • Hate Speech and Cyberbullying Detection
  • Opinion Dynamics and Social Influence
  • Social Media and Politics
  • Spam and Phishing Detection
  • Consumer Market Behavior and Pricing
  • Open Source Software Innovations
  • Biomedical Text Mining and Ontologies
  • Artificial Intelligence in Healthcare and Education
  • Auction Theory and Applications
  • AI in cancer detection

Sapienza University of Rome
2023-2024

Abstract Growing concern surrounds the impact of social media platforms on public discourse 1–4 and their influence dynamics 5–9 , especially in context toxicity 10–12 . Here, to better understand these phenomena, we use a comparative approach isolate human behavioural patterns across multiple platforms. In particular, analyse conversations different online communities, focusing identifying consistent toxic content. Drawing from an extensive dataset that spans eight over 34 years—from Usenet...

10.1038/s41586-024-07229-y article EN cc-by Nature 2024-03-20

The role of social media in information dissemination and agenda-setting has significantly expanded recent years. By offering real-time interactions, online platforms have become invaluable tools for studying societal responses to significant events as they unfold. However, reactions external developments are influenced by various factors, including the nature event environment. This study examines dynamics public discourse on digital shed light this issue. We analyzed over 12 million posts...

10.1038/s41598-024-53124-x article EN cc-by Scientific Reports 2024-02-02

Abstract The web radically changed the dissemination of information and global spread news. In this study, we aim to reconstruct connectivity patterns within nations shaping news propagation globally in 2022. We do by analyzing a dataset unprecedented size, containing 140 million articles from 183 countries related 37,802 domains GDELT database. Unlike previous research, focus on sequential mention events across various countries, thus incorporating temporal dimension into analysis networks....

10.1038/s41598-024-52076-6 article EN cc-by Scientific Reports 2024-01-17

Abstract Recently emerging large multimodal models (LMMs) utilize various types of data modalities, including text and visual inputs to generate outputs. The incorporation LMMs into clinical medicine presents unique challenges, accuracy, reliability, relevance. Here, we explore applications GPT-4V, an LMM that has been proposed for use in medicine, gastroenterology, radiology, dermatology, United States Medical Licensing Examination (USMLE) test questions. We used standardized robust...

10.1101/2024.04.12.24305744 preprint EN cc-by medRxiv (Cold Spring Harbor Laboratory) 2024-04-14

Social media platforms behave like giant arenas where users can rely on different content and express their opinions through likes, comments, shares. However, do welcome perspectives or only listen to preferred narratives? This article examines how explore the digital space allocate attention among communities two social networks, Voat Reddit. By analyzing a massive dataset of about 215 million comments posted by 16 Reddit in 2019, we find that most tend new at decreasing rate, meaning they...

10.1109/tcss.2024.3379318 article EN cc-by IEEE Transactions on Computational Social Systems 2024-04-15

Large language models (LLMs) are known to exhibit demographic biases, yet few studies systematically evaluate these biases across multiple datasets or account for confounding factors. In this work, we examine LLM alignment with human annotations in five offensive datasets, comprising approximately 220K annotations. Our findings reveal that while traits, particularly race, influence alignment, effects inconsistent and often entangled other Confounders -- such as document difficulty, annotator...

10.48550/arxiv.2411.08977 preprint EN arXiv (Cornell University) 2024-11-13

Social media platforms are like giant arenas where users can rely on different content and express their opinions through likes, comments, shares. However, do welcome perspectives or only listen to preferred narratives? This paper examines how explore the digital space allocate attention among communities two social networks, Voat Reddit. By analysing a massive dataset of about 215 million comments posted by 16 Reddit in 2019 we find that most tend new at decreasing rate, meaning they have...

10.48550/arxiv.2304.10827 preprint EN cc-by-sa arXiv (Cornell University) 2023-01-01

The web radically changed the dissemination of information and global spread news. In this study, we aim to reconstruct connectivity patterns within nations shaping news propagation globally in 2022. We do by analyzing a dataset unprecedented size, containing 140 million articles from 183 countries related 37,802 domains GDELT database. Unlike previous research, focus on sequential mention events across various countries, thus incorporating temporal dimension into analysis networks. Our...

10.48550/arxiv.2305.13769 preprint EN cc-by-sa arXiv (Cornell University) 2023-01-01

The role of social media in information dissemination and agenda-setting has significantly expanded recent years. By offering real-time interactions, online platforms have become invaluable tools for studying societal responses to significant events as they unfold. However, reactions external developments are influenced by various factors, including the nature event environment. This study examines dynamics public discourse on digital shed light this issue. We analyzed over 12 million posts...

10.48550/arxiv.2310.11116 preprint EN cc-by arXiv (Cornell University) 2023-01-01
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