Cultural Convergence: Insights into the behavior of misinformation networks on Twitter
How can the birth and evolution of ideas and communities in a network be studied over time? We use a multimodal pipeline, consisting of network mapping, topic modeling, bridging centrality, and divergence to analyze Twitter data surrounding the COVID-19 pandemic. We use network mapping to detect accounts creating content surrounding COVID-19, then Latent Dirichlet Allocation to extract topics, and bridging centrality to identify topical and non-topical bridges, before examining the distribution of each topic and bridge over time and applying Jensen-Shannon divergence of topic distributions to show communities that are converging in their topical narratives.
Code (0)
등록된 구현이 없습니다.
Tasks
MisinformationSimilar Papers 제목 키워드 기반
Stanceosaurus 2.0: Classifying Stance Towards Russian and Spanish Misinformation
The Stanceosaurus corpus (Zheng et al., 2022) was designed to provide high-quality, annotated, 5-way stance data extracted from Twitter, suitable for analyzing cross-cultural and cross-lingual misinformation. In the Stan…
Cross-Lingual TransferMisinformationStance ClassificationZero-Shot Cross-Lingual TransferCombating Misinformation in the Arab World: Challenges & Opportunities
Misinformation and disinformation pose significant risks globally, with the Arab region facing unique vulnerabilities due to geopolitical instabilities, linguistic diversity, and cultural nuances. We explore these challe…
DiversityFact CheckingMisinformationBias in the Mirror: Are LLMs opinions robust to their own adversarial attacks ?
Large language models (LLMs) inherit biases from their training data and alignment processes, influencing their responses in subtle ways. While many studies have examined these biases, little work has explored their robu…
MisinformationWhen Cow Urine Cures Constipation on YouTube: Limits of LLMs in Detecting Culture-specific Health Misinformation
Social media platforms have become primary channels for health information in the Global South. Using gomutra (cow urine) discourse on YouTube in India as a case study, we present a post-facto Large Language Model (LLM)-…
Prompt EngineeringMonolingual and Multilingual Misinformation Detection for Low-Resource Languages: A Comprehensive Survey
In today's global digital landscape, misinformation transcends linguistic boundaries, posing a significant challenge for moderation systems. Most approaches to misinformation detection are monolingual, focused on high-re…
Misinformation