Distribution of human response times

Ma, Tao; Holden, John G.; Serota, R. A.

doi:10.1002/cplx.21666

Cited by 17 publications

(10 citation statements)

References 21 publications

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“…In the context of educational assessment, the lognormal distribution has been recommended to model RT of test items (van der Linden, ). However, Ma, Holden, and Serota () demonstrate that RT distributions have power‐law tails and argue that, among the closed‐form distributions, they are best fit by the generalized inverse gamma distribution. Ihlen () investigated RT distributions for a range of simple cognitive tasks and fitted the so‐called stable distribution to RT sequences involving autocorrelation structures.…”

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confidence: 99%

Modeling Basic Writing Processes From Keystroke Logs

Guo

Deane

Rijn

et al. 2018

J Educational Measurement

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The goal of this study is to model pauses extracted from writing keystroke logs as a way of characterizing the processes students use in essay composition. Low-level timing data were modeled, the interkey interval and its subtype, the intraword duration, thought to reflect processes associated with keyboarding skills and composition fluency. Heavy-tailed probability distributions (lognormal and stable distributions) were fit to individual students' data. Both density functions fit reasonably well, and estimated parameters were found to be robust across prompts designed to assess student proficiency for the same writing purpose. In addition, estimated parameters for both density functions were statistically significantly associated with human essay scores after accounting for total time spent writing the essay, a result consistent with cognitive theory on the role of low-level processes in writing.

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confidence: 99%

Modeling Basic Writing Processes From Keystroke Logs

Guo

Deane

Rijn

et al. 2018

J Educational Measurement

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“…The distributions are not symmetrical (not normal distribution), having a longer "tail". The tail is a typical fingerprint of the complexity (multiple feedback interactions with stochastic results) (172). The complexity depends on the patient and the disease's general conditions, so the distribution curves are only orienting the reader; they could not be exact.…”

Section: Discussionmentioning

confidence: 99%

A Potential Bioelectromagnetic Method to Slow Down the Progression and Prevent the Development of Ultimate Pulmonary Fibrosis by COVID-19

Masaud¹,

Szász²,

Szász³

et al. 2020

Front. Immunol.

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IntroductionRight now, we are facing a global pandemic caused by the coronavirus SARS-CoV-2 that causes the highly contagious human disease COVID-19. The number of COVID-19 cases is increasing at an alarming rate, more and more people suffer from it, and the death toll is on the rise since December 2019, when COVID-19 has presumably appeared. We need an urgent solution for the prevention, treatment, and recovery of the involved patients.MethodsModulated electro-hyperthermia (mEHT) is known as an immuno-supportive therapy in oncology. Our proposal is to apply this method to prevent the progression of the disease after its identification, to provide treatment when necessary, and deliver rehabilitation to diminish the fibrotic—often fatal—consequences of the infection.HypothesisThe effects of mEHT, which are proven for oncological applications, could be utilized for the inactivation of the virus or for treating the fibrotic consequences. The hypothesized mEHT effects, which could have a role in the antiviral treatment, it could be applied for viral-specific immune-activation and for anti-fibrotic treatments.

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“…Miritello [1] combs literature on statistics of human behavior in information dissemination and finds that the research method based on statistics of historical data is one of the effective methods to study the law of human behavior. Ma and others [2] confirmed that the tails of RT distributions exhibit power law behavior. Therefore, through collecting and analyzing broadcast data sent by 140 Twitter users, Salathé [3] and others based on the theory of psychology conclude that the emotions from friends and social awareness are highly correlated with individual information production behavior; that is, the emotions from neighbors have an important impact on information manufacturing behavior.…”

Section: Introductionmentioning

confidence: 82%

Research on Behavior Model of Rumor Maker Based on System Dynamics

Zhu

Liu

2017

Complexity

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Laws of rumor makers' behaviors are the root of curbing rumor and effective way to block rumor occurrence. Therefore, based on system dynamics model, this paper proposed the rumors behavior evolution model of rumor makers, aimed at discovering the laws of rumor makers' behaviors to achieve rumors blocking. First, by refining the driving factors in disinformation behavior, we constructed causal diagram of disinformation behavior evolution; secondly, by means of causal diagram, we constructed stockflow diagram for quantitative analysis; finally, simulation experiment was carried out by using Vensim Personal Learning Edition software (Vensim PLE). The results showed that negative attitude is a major factor in the occurrence of disinformation behavior; personal factors are more pronounced than the factors of social and government on the impact of disinformation propensity score.

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Distribution of human response times

Cited by 17 publications

References 21 publications

Modeling Basic Writing Processes From Keystroke Logs

Modeling Basic Writing Processes From Keystroke Logs

A Potential Bioelectromagnetic Method to Slow Down the Progression and Prevent the Development of Ultimate Pulmonary Fibrosis by COVID-19

Research on Behavior Model of Rumor Maker Based on System Dynamics

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