Southern Province
Analysis of LLM Bias (Chinese Propaganda & Anti-US Sentiment) in DeepSeek-R1 vs. ChatGPT o3-mini-high
Huang, PeiHsuan, Lin, ZihWei, Imbot, Simon, Fu, WenCheng, Tu, Ethan
Large language models (LLMs) increasingly shape public understanding and civic decisions, yet their ideological neutrality is a growing concern. While existing research has explored various forms of LLM bias, a direct, cross-lingual comparison of models with differing geopolitical alignments-specifically a PRC-system model versus a non-PRC counterpart-has been lacking. This study addresses this gap by systematically evaluating DeepSeek-R1 (PRC-aligned) against ChatGPT o3-mini-high (non-PRC) for Chinese-state propaganda and anti-U.S. sentiment. We developed a novel corpus of 1,200 de-contextualized, reasoning-oriented questions derived from Chinese-language news, presented in Simplified Chinese, Traditional Chinese, and English. Answers from both models (7,200 total) were assessed using a hybrid evaluation pipeline combining rubric-guided GPT-4o scoring with human annotation. Our findings reveal significant model-level and language-dependent biases. DeepSeek-R1 consistently exhibited substantially higher proportions of both propaganda and anti-U.S. bias compared to ChatGPT o3-mini-high, which remained largely free of anti-U.S. sentiment and showed lower propaganda levels. For DeepSeek-R1, Simplified Chinese queries elicited the highest bias rates; these diminished in Traditional Chinese and were nearly absent in English. Notably, DeepSeek-R1 occasionally responded in Simplified Chinese to Traditional Chinese queries and amplified existing PRC-aligned terms in its Chinese answers, demonstrating an "invisible loudspeaker" effect. Furthermore, such biases were not confined to overtly political topics but also permeated cultural and lifestyle content, particularly in DeepSeek-R1.
- North America > United States (1.00)
- Asia > China > Beijing > Beijing (0.04)
- Asia > Taiwan > Taiwan Province > Taipei (0.04)
- (13 more...)
- Research Report > New Finding (1.00)
- Research Report > Experimental Study (0.92)
- Media (1.00)
- Government > Regional Government > North America Government > United States Government (0.92)
- Government > Military (0.92)
Disease Outbreak Detection and Forecasting: A Review of Methods and Data Sources
Babanejaddehaki, Ghazaleh, An, Aijun, Papagelis, Manos
Infectious diseases occur when pathogens from other individuals or animals infect a person, resulting in harm to both individuals and society as a whole. The outbreak of such diseases can pose a significant threat to human health. However, early detection and tracking of these outbreaks have the potential to reduce the mortality impact. To address these threats, public health authorities have endeavored to establish comprehensive mechanisms for collecting disease data. Many countries have implemented infectious disease surveillance systems, with the detection of epidemics being a primary objective. The clinical healthcare system, local/state health agencies, federal agencies, academic/professional groups, and collaborating governmental entities all play pivotal roles within this system. Moreover, nowadays, search engines and social media platforms can serve as valuable tools for monitoring disease trends. The Internet and social media have become significant platforms where users share information about their preferences and relationships. This real-time information can be harnessed to gauge the influence of ideas and societal opinions, making it highly useful across various domains and research areas, such as marketing campaigns, financial predictions, and public health, among others. This article provides a review of the existing standard methods developed by researchers for detecting outbreaks using time series data. These methods leverage various data sources, including conventional data sources and social media data or Internet data sources. The review particularly concentrates on works published within the timeframe of 2015 to 2022.
- Europe > United Kingdom (0.14)
- Asia > Japan (0.14)
- Asia > South Korea (0.14)
- (42 more...)
- Research Report > New Finding (1.00)
- Overview (1.00)
- Research Report > Experimental Study (0.67)
- Information Technology > Information Management > Search (1.00)
- Information Technology > Data Science > Data Mining (1.00)
- Information Technology > Communications > Social Media (1.00)
- (9 more...)
Artificial Intelligence is Indian Navy's new strategic frontline
In modern geo-politics the role of Indian Navy is going to be more challenging and its active participation could decide the place of India in global power play. The seminar "Swavlamban" chaired by the PM Modi on SPRINT Challenges on July 18th 2022, is showcasing the seriousness of New Delhi towards the strengthening the Indian Navy through the modern indigenous technologies. The presence of Chinses third generation research and survey ship "Yuan Wang 5" in Hambantota, Sri Lanka, is sufficient to explain that the Indo-Pacific is going to be future coliseum of geo-politics. It is provoking India to adopt modern cutting-edge naval technologies to protect the country's interest and control the foreign powers. Technology is always an important agent, which decides or redefines the war parameters with some distinctive outputs.
- Asia > Sri Lanka > Southern Province > Hambantŏṭa District > Hambantŏṭa (0.25)
- Asia > India > NCT > New Delhi (0.25)
- Indian Ocean (0.05)
- Asia > India > Uttarakhand > Dehradun (0.05)
- Government > Military > Navy (1.00)
- Government > Regional Government > Asia Government > India Government (0.84)