stem_forma_mentis — STEM forma mentis networks of students and researchers (2019)

Description

Forma mentis networks (semantic networks of free associations annotated with the emotional valence of each concept) of 159 Italian high-school students (in their final year, aged 18 to 19) and 59 early-career international STEM researchers (doctoral students and post-docs working with quantitative methods on complex systems), from Stella et al. Each participant took part in a continuous free association task, in which they gave three associated words for each of 50 cue words: 10 cues common to all participants (mathematics, complex, physics, chemistry, system, biology, life, art, school and university), and 40 drawn at random from 390 frequent words of the Wikipedia pages on complex systems, physics, mathematics, biology, chemistry and psychology. The students answered in Italian, and the researchers in English. Each node is a word (converted to lowercase, spell-checked, and normalized to singular forms), and an undirected edge connects a cue to an associated response. Afterwards, the participants rated the valence of the cues and responses on a scale from 1 (very negative) to 5 (very positive). The following networks are included:

students: all associations given by the students.
students_filtered: only the associations given by at least two different students.
researchers: all associations given by the researchers.
researchers_filtered: the filtered network of the researchers, as distributed with the data (the paper analyzes only the unfiltered network of researchers, due to the smaller sample size).

The networks have the following properties:

Nodes: name, the word; valence, the valence category of the word ("Positive", "Neutral" or "Negative"). A word was labelled as positive (negative) if its median valence score was higher (lower) than that of the remaining words, according to a Kruskal-Wallis test at significance level 0.1, and neutral otherwise. The labels come from the valence files of the complete networks, and are empty for the few words that are missing from them (1 word in each complete network, and 13 in each filtered network, which contain a few words in different forms).

Tags

Informational Language Unweighted Metadata

Citation

M. Stella, S. De Nigris, A. Aloric, C. S. Q. Siew, "Forma mentis networks quantify crucial differences in STEM perception between students and experts." PLOS ONE 14(10), e0222870 (2019) 10.1371/journal.pone.0222870 Sci-Hub

Upstream URL OK

https://osf.io/xyfwg/

Upstream license

Creative Commons Attribution 4.0 International (CC BY 4.0), https://creativecommons.org/licenses/by/4.0/

Networks

Tip: click on a column header to sort the list, or hover over it for a description.

Column legend

$\left<k\right>$: Mean degree
$\sigma_k$: Standard deviation of the degrees
$\lambda_h$: Largest eigenvalue of the Hashimoto (non-backtracking) matrix
$\tau$: Random walk mixing time
$r$: Degree assortativity
$c$: Global clustering coefficient
$\oslash$: (Pseudo-) diameter
$S$: Relative size of the largest component
NPs: Node properties
EPs: Edge properties

Name	Nodes	Edges	$\left<k\right>$	$\sigma_k$	$\lambda_h$	$\tau$	$r$	$c$	$\oslash$	$S$	Kind	Mode	NPs	gt	GraphML	GML	csv
students	4,483	10,628	4.74	10.10	21.82	5.56	-0.34	0.04	7	1.00	Undirected	Unipartite	name valence	42 KiB	63 KiB	63 KiB	59 KiB
students_filtered	1,644	2,837	3.45	4.67	9.27	32.89	-0.09	0.06	11	1.00	Undirected	Unipartite	name valence	15 KiB	22 KiB	22 KiB	20 KiB
researchers	1,616	3,045	3.77	5.87	11.71	39.53	-0.05	0.04	10	1.00	Undirected	Unipartite	name valence	15 KiB	22 KiB	22 KiB	21 KiB
researchers_filtered	146	159	2.18	2.11	2.58	128.39	-0.13	0.04	19	1.00	Undirected	Unipartite	name valence	2 KiB	3 KiB	3 KiB	3 KiB