jmatayoshi/affect-transitions

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Evidence · 1 claim (1 for) · 1 study (1 theoretical), q2 · 0 of 1 report an effect size · 1 claim rests on one study

Description

An open-source Python module by Jeffrey Matayoshi for simulating affect transitions and computing L and L* statistics.

Components

• Python module for affect transition simulations and L/L computation (jmatayoshi/affect-transitions)**: The article references a released software artifact: "See Matayoshi (2020) for a Python module for performing these simulations and computing L and L∗ values." The reference list identifies it as "jmatayoshi/affect-transitions: Release 1.0.0." The module supports the simulation-based evaluation of L described in Section 6 and computation of both statistics on affect sequences. (Jeffrey Matayoshi et al. (2020))

Claims

• Theoretical ranges differ sharply: L with self-transitions removed is bounded below by −1 (individual base rates) or −2 (averaged), while L* is bounded by −k+1 (individual) or has no finite lower bound (averaged) [+W]

Related Products and Programmes

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Key Sources

• Jeffrey Matayoshi and Shamya Karumbaiah. (2020). Adjusting the L Statistic when Self-Transitions are Excluded in Affect Dynamics. Journal of Educational Data Mining, Volume 12, No 4. https://jedm.educationaldatamining.org/index.php/JEDM/article/view/478

Page metadata

Field	Value
type	product
id	jmatayoshiaffect-transitions
title	jmatayoshi/affect-transitions
description	An open-source Python module by Jeffrey Matayoshi for simulating affect transitions and computing L and L* statistics.
status	review
moved_from	element/affect-transitions-python-module
product_kind	software
generated	by process:sweep-kinds on 2026-10-10
trust	unverified — no one has confirmed this page's content
sources	1 — jeffrey-matayoshi-and-shamya-karumbaiah-2020

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