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.
MGM improves media profiling by integrating textual and structural features.
A variety of approaches have been proposed to automatically infer the profiles of users from their digital footprint in social media. Most of the proposed approaches focus on mining a single type of information, while ignoring other sources of available user-generated content (UGC). In this paper, we propose a mechanis…
Study of fastest paths in anisotropic media via Finsler geometry.
Paper improves gender detection on social media using deep learning.
This paper revisits the problem of recovering a smooth, isotropic, layered wave speed profile from surface traveltime information. While it is classic knowledge that the diving (refracted) rays classically determine the wave speed in a weakly well-posed fashion via the Abel transform, we show in this paper that travelt…
Predicts morning traffic congestion using social media data from the previous evening.
Big spatio-temporal datasets, available through both open and administrative data sources, offer significant potential for social science research. The magnitude of the data allows for increased resolution and analysis at individual level. While there are recent advances in forecasting techniques for highly granular te…
SINN combines social science and deep learning for predicting opinion dynamics.
In general, anomaly detection is the problem of distinguishing between normal data samples with well defined patterns or signatures and those that do not conform to the expected profiles. Financial transactions, customer reviews, social media posts are all characterized by relational information. In these networks, fra…
New equations for Cosserat media motions derived from bundle automorphisms.
Social media are nowadays one of the main news sources for millions of people around the globe due to their low cost, easy access and rapid dissemination. This however comes at the cost of dubious trustworthiness and significant risk of exposure to 'fake news', intentionally written to mislead the readers. Automaticall…
This article asks how planning scholarship may effectively gain impact in planning practice through media exposure. In liberal democracies the public sphere is dominated by mass media. Therefore, working with such media is a prerequisite for effective public impact of planning research. Using the example of megaproject…
Study compares sentiment spillover networks from news and social media in tech companies.
As a highlighting research topic in the multimedia area, cross-media retrieval aims to capture the complex correlations among multiple media types. Learning better shared representation and distance metric for multimedia data is important to boost the cross-media retrieval. Motivated by the strong ability of deep neura…
The paper introduces new uniformity and homogeneity concepts for Cosserat media.
Social media enhances or diminishes scientific status, depending on usage.
Media tone around earnings announcements predicts stock returns.
Study applies market microstructure to Cuban informal currency market, finding market makers improve liquidity.
EmTract extracts emotions from financial social media text.
Online social networks offer a new way to investigate financial markets' dynamics by enabling the large-scale analysis of investors' collective behavior. We provide empirical evidence that suggests social media and stock markets have a nonlinear causal relationship. We take advantage of an extensive data set composed o…
This paper studies how social media posts, especially by executives, affect stock prices.
A dataset for detecting online hate speech from YouTube and Reddit comments.
Social media reduces individual investors' disposition effect through negative information.
Deep learning ensemble detects social media rumors faster.
The tools of presymplectic geometry are used to study light rays trajectories in anisotropic media.
Study travel time tomography for transversely isotropic media using modified pseudodifferential calculus.
Deep learning predicts stock movements using social media data.
Study finds meme stocks have unique price and social media dynamics.
Study finds social media investor emotions predict stock prices.
Study uses social media to analyze COVID-19 impact.
Study shows social media impacts shareholder returns on ESG risks.
Model financial markets with social media influences using hierarchical networks.
The combination of large open data sources with machine learning approaches presents a potentially powerful way to predict events such as protest or social unrest. However, accounting for uncertainty in such models, particularly when using diverse, unstructured datasets such as social media, is essential to guarantee t…
Sentiment analysis from news and social media predicts forex market movements.
Systematic review of ML models for detecting social media deception.
Study uses multiple online media to predict crude oil prices.
Online harassment is a significant social problem. Prevention of online harassment requires rapid detection of harassing, offensive, and negative social media posts. In this paper, we propose the use of word embedding models to identify offensive and harassing social media messages in two aspects: detecting fast-changi…
Detecting depression early from social media texts.
The notions of uniformity and homogeneity of elastic materials are reviewed in terms of Lie groupoids and frame bundles. This framework is also extended to consider the case Functionally Graded Media, which allows us to obtain some homogeneity conditions.
Studies across many disciplines have shown that lexical choice can affect audience perception. For example, how users describe themselves in a social media profile can affect their perceived socio-economic status. However, we lack general methods for estimating the causal effect of lexical choice on the perception of a…
In this paper, we study the discrete Morse flow for the Ricci flow on football, which is the 2-sphere with removed north and south poles and with the metric of constant scalar curvature, and and for Porous media equation on a bounded regular domain in the plane. We show that with a suitable assumption about $g(0)…
The rise in popularity of major social media platforms have enabled people to share photos and textual information about their daily life. One of the popular topics about which information is shared is food. Since a lot of media about food are attributed to particular locations and restaurants, information like spatio-…
In this work, we analyze the flow filtration process of slightly compressible fluids in porous media containing man made fractures with complex geometries. We model the coupled fracture-porous media system where the linear Darcy flow is considered in porous media and the nonlinear Forchheimer equation is used inside th…
GCAN detects fake news on social media with explanations.
Opinion polls have been the bridge between public opinion and politicians in elections. However, developing surveys to disclose people's feedback with respect to economic issues is limited, expensive, and time-consuming. In recent years, social media such as Twitter has enabled people to share their opinions regarding …
A method to produce personalized classification models to automatically review online dating profiles on Tinder is proposed, based on the user's historical preference. The method takes advantage of a FaceNet facial classification model to extract features which may be related to facial attractiveness. The embeddings fr…
Profile entropy measures learnability and compressibility of discrete distributions.
A method to describe Riemann surfaces using graph profiles is proposed.