A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.
Benchmark evaluates financial misinformation detection models, revealing weaknesses without external context.
System detects financial misinformation and generates clear explanations.
AI threatens financial stability through misuse and stealth adoption.
Study analyzes misinformation on social media during COVID-19.
ICA model detects misinformation during high impact events like COVID-19.
This paper combines data-driven and model-driven methods for real-time misinformation detection. Our algorithm, named QuickStop, is an optimal stopping algorithm based on a probabilistic information spreading model obtained from labeled data. The algorithm consists of an offline machine learning algorithm for learning …
Online social networking sites are experimenting with the following crowd-powered procedure to reduce the spread of fake news and misinformation: whenever a user is exposed to a story through her feed, she can flag the story as misinformation and, if the story receives enough flags, it is sent to a trusted third party …
Recent years have witnessed a significant increase in the online sharing of medical information, with videos representing a large fraction of such online sources. Previous studies have however shown that more than half of the health-related videos on platforms such as YouTube contain misleading information and biases. …
HiJoD detects misinformation using multiple aspects and outperforms state-of-the-art methods.
This paper argues, first, that a major problem in the planning of large infrastructure projects is the high level of misinformation about costs and benefits that decision makers face in deciding whether to build, and the high risks such misinformation generates. Second, it explores the causes of misinformation and risk…
Study tackles misinformation on Twitter by detecting and classifying rumors.
StratLearner learns strategies to prevent misinformation in social networks.
Adaptive Misinformation defends against model stealing attacks by sending incorrect predictions for OOD queries.
Study compares deepfake detection models, finding GenConViT superior.
A key challenge for Bitcoin cryptocurrency holders, such as startups using ICOs to raise funding, is managing their FX risk. Specifically, a misinformed decision to convert Bitcoin to fiat currency could, by itself, cost USD millions. In contrast to financial exchanges, Blockchain based crypto-currencies expose the ent…
Kernel analysis reveals rumor truth from diffusion patterns alone.
Automatically assesses the quality of online health articles.
Adaptive testing segments watermarked text from LLMs.
Systematic review of ML models for detecting social media deception.
A new framework maximizes influence spread in social networks by accounting for inter-community diffusion.
Study explores rumor spread on Twitter using supervised learning.
Ranking models are typically designed to provide rankings that optimize some measure of immediate utility to the users. As a result, they have been unable to anticipate an increasing number of undesirable long-term consequences of their proposed rankings, from fueling the spread of misinformation and increasing polariz…
While the purpose of most fake news is misinformation and political propaganda, our team sees it as a new type of myth that is created by people in the age of internet identities and artificial intelligence. Seeking insights on the fear and desire hidden underneath these modified or generated stories, we use machine le…
Automated model assesses online health info quality using machine learning.
Managing large-scale transportation infrastructure projects is difficult due to frequent misinformation about the costs which results in large cost overruns that often threaten the overall project viability. This paper investigates the explanations for cost overruns that are given in the literature. Overall, four categ…
Online health communities are a valuable source of information for patients and physicians. However, such user-generated resources are often plagued by inaccuracies and misinformation. In this work we propose a method for automatically establishing the credibility of user-generated medical statements and the trustworth…
Back cover text: Megaprojects and Risk provides the first detailed examination of the phenomenon of megaprojects. It is a fascinating account of how the promoters of multibillion-dollar megaprojects systematically and self-servingly misinform parliaments, the public and the media in order to get projects approved and b…
The prevalence of social media has made information sharing possible across the globe. The downside, unfortunately, is the wide spread of misinformation. Methods applied in most previous rumor classifiers give an equal weight, or attention, to words in the microblog, and do not take the context beyond microblog content…
The proliferation of fake news on social media has opened up new directions of research for timely identification and containment of fake news, and mitigation of its widespread impact on public opinion. While much of the earlier research was focused on identification of fake news based on its contents or by exploiting …
The paper examines how algorithmic classification affects behavior and proposes democratizing stakes to mitigate predatory practices.
The paper discusses decades of stock market manipulation and its benefits.
SD-SCMs generate counterfactual data for causal inference benchmarks.
Study detects fake news in Brazilian Portuguese using machine learning.
Paper introduces a new algorithm to detect LLM-generated text.
While social networks can provide an ideal platform for up-to-date information from individuals across the world, it has also proved to be a place where rumours fester and accidental or deliberate misinformation often emerges. In this article, we aim to support the task of making sense from social media data, and speci…
Framework detects fake news using weak social signals from multiple sources.
CoT-UQ improves LLM uncertainty quantification by integrating reasoning steps.
ADD embeds a 48-bit message into images, achieving high accuracy and speed.
Develops an anytime-valid framework for optimal policy identification from logged contextual bandit data.
Study examines financial structure's impact on non-financial firms' growth in Kenya.
Study shows financial literacy, social capital, and financial tech positively impact financial inclusion of Indonesian students.
Fake news may be intentionally created to promote economic, political and social interests, and can lead to negative impacts on humans beliefs and decisions. Hence, detection of fake news is an emerging problem that has become extremely prevalent during the last few years. Most existing works on this topic focus on man…
Financial planners helped preserve and increase household net financial assets during the Great Recession.
Motivated by recent financial crises significant research efforts have been put into studying contagion effects and herding behaviour in financial markets. Much less has been said about influence of financial news on financial markets. We propose a novel measure of collective behaviour in financial news on the Web, New…
BERT improves machines' ethical and moral decision-making.
Proposes LSTM for financial market trend forecasting.
Financial system being the place of metting capital flows (equality between saving and investment), a volatility of capital flows can destroy the robustness and good working of financial system, it means subvert financial stability. The same a weak financial system, few regulated and bad manage can exacerbate volatilit…
We consider dynamics of financial markets as dynamics of expectations and discuss such a dynamics from the point of view of phenomenological thermodynamics. We describe a financial Carnot cycle and the financial analogue of a heat machine. We see, that while in physics a perpetuum mobile is absolutely impossible, in ec…