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Newspaper headlines contribute severely and have an influence on the social media. This work studies the durability of impact of verbs and adjectives on headlines and determine the factors which are responsible for its nature of influence…

Computation and Language · Computer Science 2019-09-06 Aneek Barman Roy , Baolei Chen , Siddharth Tiwari , Zihan Huang

Causality is a non-obvious concept that is often considered to be related to temporality. In this paper we present a number of past and present approaches to the definition of temporality and causality from philosophical, physical, and…

Machine Learning · Computer Science 2010-07-16 Kamran Karimi

Given two time series, can one tell, in a rigorous and quantitative way, the cause and effect between them? Based on a recently rigorized physical notion namely information flow, we arrive at a concise formula and give this challenging…

Methodology · Statistics 2014-03-27 X. San Liang

We study theoretically the spatial correlations between the intensities measured at the input and output planes of a disordered scattering medium. We show that at large optical thicknesses, a long-range spatial correlation persists and…

Optics · Physics 2015-09-23 N. Fayard , A. Cazé , R. Pierrat , R. Carminati

We present an overview of the decision-theoretic framework of statistical causality, which is well-suited for formulating and solving problems of determining the effects of applied causes. The approach is described in detail, and is related…

Statistics Theory · Mathematics 2020-04-28 A. Philip Dawid

Events in distributed systems include sending or receiving messages, or changing some state in a node. Not all events are related, but some events can cause and influence how other, later events, occur. For instance, a reply to a received…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-12-17 Carlos Baquero

We start from the well-known form of the interval of the special relativity, stare it, and build up an attempt to implement the causality from it. Some features appear to be new, they involve the mass of the particle and the structure of…

High Energy Physics - Theory · Physics 2007-05-23 Ricardo Bentin

Causality is omnipresent in scientists' verbalisations of their understanding, even though we have no formal consensual scientific definition for it. In Automata Networks, it suffices to say that automata "influence" one another to…

Other Computer Science · Computer Science 2016-10-28 Mathilde Noual

Causal inference for air pollution mixtures is an increasingly important issue with appreciable challenges. When the exposure is a multivariate mixture, there are many exposure contrasts that may be of nominal interest for causal effect…

Methodology · Statistics 2024-02-01 Joseph Antonelli , Corwin Zigler

This paper deals with the problem of evaluating the causal effect using observational data in the presence of an unobserved exposure/ outcome variable, when cause-effect relationships between variables can be described as a directed acyclic…

Methodology · Statistics 2012-06-18 Manabu Kuroki , Zhihong Cai

In a causal world the direction of the time arrow dictates how past causal events in a variable $X$ produce future effects in $Y$. $X$ is said to cause an effect in $Y$, if the predictability (uncertainty) about the future states of $Y$…

Chaotic Dynamics · Physics 2018-07-24 Ezequiel Bianco-Martinez , Murilo S. Baptista

Identifying and communicating relationships between causes and effects is important for understanding our world, but is affected by language structure, cognitive and emotional biases, and the properties of the communication medium. Despite…

Computers and Society · Computer Science 2017-02-21 Thomas C. McAndrew , Joshua C. Bongard , Christopher M. Danforth , Peter S. Dodds , Paul D. H. Hines , James P. Bagrow

We consider the problem of assessing whether, in an individual case, there is a causal relationship between an observed exposure and a response variable. When data are available on similar individuals we may be able to estimate prospective…

Statistics Theory · Mathematics 2023-11-15 Monica Musio , Philip Dawid

We propose a set of causal estimands that we call the "mediated probabilities of causation." These estimands quantify the probabilities that an observed negative outcome was induced via a mediating pathway versus a direct pathway in a…

Methodology · Statistics 2025-02-14 Max Rubinstein , Maria Cuellar , Daniel Malinsky

The theory of actual causality, defined by Halpern and Pearl, and its quantitative measure - the degree of responsibility - was shown to be extremely useful in various areas of computer science due to a good match between the results it…

Software Engineering · Computer Science 2016-08-30 Hana Chockler

This essay is the first systematic account of causal relationships between measurement instruments and the data they elicit in the social sciences. This problem of reflexive measurement is pervasive and profoundly affects social scientific…

Physics and Society · Physics 2022-08-15 James Michelson

Causality has become a fundamental approach for explaining the relationships between events, phenomena, and outcomes in various fields of study. It has invaded various fields and applications, such as medicine, healthcare, economics,…

Artificial Intelligence · Computer Science 2024-03-19 Abraham Itzhak Weinberg , Cristiano Premebida , Diego Resende Faria

We study electromagnetic wave propagation in mediums in which the effective relative permittivity and the effective relative permeability are allowed to take any value in the upper half of the complex plane. A general condition is derived…

Classical Physics · Physics 2009-11-07 M. W. McCall , A. Lakhtakia , W. S. Weiglhofer

Over the past two decades, the rapid surge in data-intensive computational techniques for statistical modeling may have had the effect of diminishing the use of applied mathematics in causal scientific inquiry. In this paper, co-authored by…

History and Philosophy of Physics · Physics 2026-05-13 Marzieh Asgari-Targhi , Amene Asgari-Targhi , Mahboubeh Asgari-Targhi , Edward J. , Hall

We propose a definition of causality for time series in terms of the effect of an intervention in one component of a multivariate time series on another component at some later point in time. Conditions for identifiability, comparable to…

Methodology · Statistics 2012-06-26 Michael Eichler , Vanessa Didelez