Media tone around earnings announcements predicts stock returns.
problem Determining if media tone around earnings announcements provides useful information for stock prices.
method Conducted an event study on media tone around earnings announcements for nonfinancial S&P 500 firms.
result Media tone around earnings announcements predicts abnormal stock returns.
Study uses multiple online media to predict crude oil prices.
problem Forecasting crude oil prices using online media.
method Semantic analysis and ARIMAX models on Twitter, Google Trends, Wikipedia, and GDELT.
result Combined analysis from four platforms improves price prediction.
Study finds bounds for fundamental tone on special Riemannian manifolds.
problem Finding bounds for fundamental tones on specific Riemannian manifolds.
method Developed a general lower bound for the fundamental tone of the p-Laplacian.
result Results applied to negatively curved manifolds, warped products, and Riemannian submersions.
The aim of this paper is to obtain the fundamental tone for minimal submanifolds of the Euclidean or hyperbolic space under certain restrictions on the extrinsic curvature. We show some sufficient conditions on the norm of the second fundamental form that allow us to obtain the same upper and lower bound for the fundam…
Research shows SBP's tone impacts stock market returns positively or negatively.
problem Impact of State Bank of Pakistan's monetary policy communications on stock market.
method Sentiment analysis and high frequency stock market returns analysis.
result Positive or negative tone in SBP communications affects stock returns positively or negatively.
The paper introduces two-tone colorings for links and shows conditions for surjective dihedral representations.
problem The challenge is to find conditions for links to admit surjective dihedral representations.
method The method involves introducing two-tone colorings and providing conditions for the link groups to admit such representations.
result Any link with at least 3 components admits a surjective homomorphism to the dihedral group of arbitrary degree.
The paper investigates skin tone estimation and its impact on dermatology model performance.
problem The impact of skin tone on dermatology model performance is not well understood.
method The authors use individual typology angle (ITA) to estimate skin tone in dermatology datasets and analyze model performance.
result There is no measurable correlation between model performance and ITA values.
The study predicts how discussions in mental disorder Reddit communities affect users' emotional states.
problem Improving mental health conditions through social support analysis.
method Text embedding techniques and RNNs for predicting emotional tone shifts.
result Users' emotional states can improve due to social support, as evidenced by positive comments following negative posts.
Develops a Barta theorem for p-Laplacian on manifolds.
problem Sharp lower bounds for p-fundamental tone on Riemannian manifolds.
method Extends Barta-type formulation to nonlinear setting on Riemannian manifolds.
result Sharp lower bounds for p-fundamental tone without boundary regularity assumptions.
We give lower bounds for the fundamental tone of open sets in submanifolds with locally bounded mean curvature in N×R, where N is an n-dimensional complete Riemannian manifold with radial sectional curvature KN≤κ. When the immersion is minimal our estimates are sharp. We also show that …
In this work, we investigate whether state-of-the-art object detection systems have equitable predictive performance on pedestrians with different skin tones. This work is motivated by many recent examples of ML and vision systems displaying higher error rates for certain demographic groups than others. We annotate an …
News sentiment in U.S. economic newspapers has become more persistent over 45 years.
problem Understanding the temporal dynamics of U.S. economic news sentiment over time.
method Daily economic news sentiment index from 1980-2025, analyzed using sentiment indexes.
result News sentiment states have become more persistent, with longer residence times in optimistic or pessimistic regimes.
Paper proposes a fast method to detect changes in audiometric function.
problem Detecting changes in psychometric function estimation quickly and accurately.
method Bayesian active differential selection for pure-tone audiogram testing.
result Fewer tones can detect changes in audiometric function with high confidence.
We study Lord Rayleigh's problem for clamped plates on an arbitrary n-dimensional (n≥2) Cartan-Hadamard manifold (M,g) with sectional curvature K≤−κ2 for some κ≥0. We first prove a McKean-type spectral gap estimate, i.e. the fundamental tone of any domain in (M,g) is universally bounde…
We study the volume of extrinsic balls and the capacity of extrinsic annuli in minimal submanifolds which are properly immersed with controlled radial sectional curvatures into an ambient manifold with a pole. The key results are concerned with the comparison of those volumes and capacities with the corresponding entit…
Algorithm finds frequencies, amplitudes, and phases of sinusoids in noisy data.
problem Finding frequencies, amplitudes, and phases of sinusoids in noisy data.
method Maximum likelihood approach to estimate tone parameters from contaminated observations. Successively estimates frequencies and jointly optimizes amplitudes and phases.
result Near-linear computational complexity (O(N)) for estimating M number of sinusoidal sources. New equations for Cosserat media motions derived from bundle automorphisms.
problem Modeling deformations in Cosserat media.
method Euler-type equations derived from SO(3)-bundle automorphisms.
result Presented new equations for Cosserat media motions.
Analysts use vague language in reports to convey useful information about future payoffs.
problem Lack of precise numerical forecasts in analyst reports.
method Empirical analysis of analyst reports to assess the predictive power of linguistic tone.
result The textual tone of analyst reports has predictive power for forecast errors and subsequent revisions, especially when language is vague and uncertainty is high.
We compute the first Dirichlet eigenvalue of a geodesic ball in a rotationally symmetric model space in terms of the moment spectrum for the Brownian motion exit times from the ball. This expression implies an estimate as exact as you want for the first Dirichlet eigenvalue of a geodesic ball in these rotationally symm…
We give lower bounds for the fundamental tone of open sets in minimal submanifolds immersed into warped product spaces of type Nn×fQq, where f∈C∞(N). We also study the essential spectrum of these minimal submanifolds.
We obtain geometric estimates for the first eigenvalue and the fundamental tone of the p-laplacian on manifolds in terms of admissible vector fields. Also, we defined a new spectral invariant and we show its relation with the geometry of the manifold.
We establish a method for giving lower bounds for the fundamental tone of elliptic operators in divergence form in terms of the divergence of vector fields. We then apply this method to the Lr operator associated to immersed hypersurfaces with locally bounded (r+1)-th mean curvature Hr+1 of the space forms …
Extremal spectral properties of the Lawson tori are studied. A Lawson torus carries an extremal metric for some eigenvalue of the Laplace-Beltrami operator. The main result of this paper is that the number of this eigenvalue is expressed in terms of fundamental tones of auxiliary periodic Sturm-Liouville problems.
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.
problem Understanding how sentiment information flows between companies through news and social media.
method Network-based transfer entropy method to measure and compare sentiment spillover.
result News shows stronger information flow among tech companies after COVID-19.
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.
problem Characterizing uniformity and homogeneity in Cosserat media.
method Using groupoids and smooth distributions, the authors derive three canonical equations to characterize uniformity and homogeneity.
result The paper provides a unique and maximal division of Cosserat media into uniform and second-grade parts.
Social media enhances or diminishes scientific status, depending on usage.
problem Impact of social media on scientific stratification and mobility.
method Logistic Attribution Analysis combining statistical and machine learning methods.
result Social media promotes stratification and mobility, but beyond a threshold, it negatively impacts status.
In this paper we obtain lower bound estimates of the spectrum of Laplace-Beltrami operator on complete submanifolds with bounded mean curvature, whose ambient space admits a Riemannian submersion over a Riemannian manifold with negative sectional curvature. Our main theorem generalizes many previous known estimates and…
In this paper, we investigate submanifolds with locally bounded mean curvature in Hadamard manifolds, product manifolds N×R, submanifolds with bounded φ-mean curvature in the hyperbolic space, and successfully give lower bounds for the weighted fundamental tone and the first eigenvalue of the $p…
Improved binning technique boosts nUV measure performance.
problem Improving the performance of the nUV measure in real applications.
method Introduced the nUV measure, provided theoretical optimal binning techniques, and proposed algorithms for approximate solutions.
result Approximate binning techniques show 4-13% increase in AUC scores with statistical significance.
EmTract extracts emotions from financial social media text.
problem Understanding investor emotions in financial markets.
method Annotated data, DistilBERT model, embedding space augmentation.
result EmTract outperforms existing emotion classifiers.
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.
problem Predicting stock market movements using social media data.
method Integrated sentiment analysis of Twitter and Reddit posts with historical stock data using time series models and deep learning.
result Improvements in stock price prediction when social media data, especially executive posts, are included.
Paper proposes using word embeddings to detect trolls in social media debates.
problem Preventing online harassment through rapid detection of offensive posts.
method Word embedding models for identifying fast-changing topics and negative content.
result GloVe model helps in discovering new keywords for trolling detection.
The aim of this work is to link the quasiconformal geometry of a Euclidean domain U to the spectral properties of its Dirichlet integral $\D$, through the algebra of multipliers $\M(H^{1,2}(U))$ of the Sobolev space. In the main result we prove that a homeomorphism γ:U→γ(U) between Euclidean domains, giving rise …
Social media reduces individual investors' disposition effect through negative information.
problem The disposition effect in individual investors selling profitable assets too early and holding onto losing assets for too long.
method Analysis of post data and trading data from Xueqiu.com.
result Social media information significantly reduces the disposition effect.
Deep learning ensemble detects social media rumors faster.
problem Timely detection of rumors on social media platforms.
method Ensemble model using deep neural networks and time-series tweet data.
result Improved rumor detection performance by 7.9%.
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.
problem Travel time tomography problem for transversely isotropic media.
method Modified scattering pseudodifferential calculus to solve the tomography problem.
result Construction and use of modified pseudodifferential calculus to solve the tomography problem.
Deep learning predicts stock movements using social media data.
problem Predicting stock movements with traditional methods is challenging.
method Graph neural network combining financial data and social media.
result Improvement of 28% in cumulative returns.
Study finds meme stocks have unique price and social media dynamics.
problem Exploring unique properties of meme stocks.
method Regime-switching cointegration model.
result Meme stocks exhibit a distinct 'mementum' compared to other high-volume stocks.
Paper improves gender detection on social media using deep learning.
problem Traditional classifiers struggle with social media data volume.
method Ensemble deep learning with multi-model architectures.
result Improved gender detection accuracy on social media posts.
Study tackles hate speech against journalists on social media.
problem Hate speech against journalists on social media remains prevalent despite efforts.
method Defined journalist-specific hate speech, annotated tweets, trained deep learning models, and proposed an ensemble model.
result Proposed ensemble model outperforms individual models in detecting journalist-targeted hate speech.
Study finds social media investor emotions predict stock prices.
problem Validation of social media sentiment models in predicting market behavior.
method Employed EmTract, an emotion model, to test social media sentiment against lab experiments.
result Firm-specific investor emotions forecast daily asset price movements.
Study uses social media to analyze COVID-19 impact.
problem Understanding the global impact of COVID-19.
method Machine learning and linguistic tools to analyze social media posts.
result Automatic detection of positive reports of COVID-19.
Study shows social media impacts shareholder returns on ESG risks.
problem Investor sentiment and public opinion on ESG risks.
method Event study design using social media data.
result Statistically significant reduction in abnormal returns after ESG-risk events.
Additive asynchronous and cyclostationary impulsive noise limits communication performance in OFDM powerline communication (PLC) systems. Conventional OFDM receivers assume additive white Gaussian noise and hence experience degradation in communication performance in impulsive noise. Alternate designs assume a parametr…