Power-Law Behavior in the Inter-Event Times of Word Occurrences
Open Access
- 15 March 2026
- journal article
- research article
- Published by MDPI AG in Applied Sciences
- Vol. 16 (6) , 2818
Abstract
In this paper, we investigate the inter-event times of frequent words observed in 17 academic books, where the inter-event time is defined as the number of sentences between two successive appearances of a given word. Our results show that the distributions of inter-event times for frequent words can be classified into three types: the exponential distribution, the q-exponential distribution, and the power-law distribution. To examine the generative mechanisms underlying these three types, we conducted text generation simulations and found that combining two mechanisms for word selection—priority-based selection and randomized selection—is sufficient to reproduce the observed three distribution types. In particular, the priority-based selection mechanism, in which words for a constructed sentence are chosen mechanically according to predefined priorities assigned to each word, is identified as the underlying mechanism of the power-law distribution of inter-event times. We also discuss in detail the relationship between the priority-based selection mechanism and the multivariate Hawkes process, which effectively captures mutual correlations among occurrences of important words.Keywords
Funding Information
- JSPS KAKENHI (24K15198)
This publication has 47 references indexed in Scilit:
- Inference of multivariate exponential Hawkes processes with inhibition and application to neuronal activityStatistics and Computing, 2023
- A stochastic model of word occurrences in hierarchically structured written textsSN Applied Sciences, 2022
- A Note on Likelihood Ratio Tests for Models with Latent VariablesPsychometrika, 2020
- Simulation of pseudo-text synthesis for generating words with long-range dynamic correlationsSN Applied Sciences, 2020
- Theory of earthquakes interevent times applied to financial marketsPhysica A: Statistical Mechanics and its Applications, 2017
- Stochastic Processes2013
- Information Criteria and Statistical Modeling2008
- Modelling security market events in continuous time: Intensity based, multivariate point process modelsJournal of Econometrics, 2007
- A First Course in Stochastic Models2003
- Possible generalization of Boltzmann-Gibbs statisticsJournal of Statistical Physics, 1988