word_assoc_usf — USF free association norms (1998)

Description

A directed network of free word associations, from the University of South Florida (USF) free association norms, collected by D. L. Nelson, C. L. McEvoy and T. A. Schreiber from 1973 onwards with more than 6,000 participants in the United States, and made available in 1998. Participants were given a printed cue word and asked to write the first word that came to mind that was meaningfully related or strongly associated to it; each cue was normed by a group of about 150 participants (each participant saw at most about 100 cues). Nodes are words (10,617 words, of which 5,018 were normed as cues), and a directed edge from a cue to a target indicates that the target was given as a response to the cue by at least two participants (responses given by a single participant are not included in the norms). There are 72,176 cue-target pairs, including 4 in which a cue was given as its own response (self-loops).

Edge properties (as in the "Appendix A" files of the norms):

group_size: number of participants in the group that normed the cue (#G).
n_responses: number of participants that produced the target in response to the cue (#P).
fsg: forward (cue-to-target) strength, i.e. n_responses / group_size.
bsg: backward (target-to-cue) strength, the forward strength of the reverse pair (zero if the target did not produce the cue; NaN if the target was not normed).
msg: mediated (two-step) strength, the sum over mediating words m of the products of the cue-to-m and m-to-target strengths (NaN if the target was not normed).
osg: overlapping associate strength, the sum over the associates shared by the cue and the target of the products of their strengths to them (NaN if the target was not normed).
n_mediators, n_mediators_unnormed: number of mediating words, and of potential mediators that were not normed (so that msg may be underestimated).
n_overlaps, n_overlaps_unnormed: number of associates shared by cue and target, and of shared associates that were not normed.

Vertex properties (word attributes, available only for the normed words, otherwise they are -1, NaN or empty):

word: the word.
normed: whether the word was normed as a cue.
set_size: number of different responses given by two or more participants to the word.
frequency: printed frequency of the word, from the Kučera and Francis (1967) norms (a few very frequent words, such as "A", have the value 9999).
concreteness: concreteness rating (1 to 7), mostly from the Paivio, Yuille and Madigan (1968) or Toglia and Battig (1978) norms.
homograph: whether the word is (likely) a homograph, given as the initial of the source of homograph norms (empty if not a homograph).
part_of_speech: part of speech of the first dictionary entry of the word (N: noun, V: verb, AJ: adjective, AD: adverb, P: pronoun, PP: preposition, I: interjection, C: conjunction).
mean_connectivity: mean number of connections among the associates of the word.
resonance_probability: fraction of the associates of the word that produce the word as an associate.
resonance_strength: sum over associates of the products of the word-to-associate and associate-to-word strengths.
use_code: 1 if all important associates of the word were normed (recommended for experiments), 0 otherwise.

A version of this network without weights or attributes (and without the self-loops) is also distributed by the Laboratory for Web Algorithmics as wordassociation-2011.

Tags

Informational Language Weighted Metadata

Citation

D. L. Nelson, C. L. McEvoy, and T. A. Schreiber, "The University of South Florida free association, rhyme, and word fragment norms." Behavior Research Methods, Instruments, & Computers 36(3), 402-407 (2004). 10.3758/BF03195588 Sci-Hub

Upstream URL OK

http://w3.usf.edu/FreeAssociation/

Networks

Tip: hover over a column header 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	EPs	gt	GraphML	GML	csv
word_assoc_usf	10,617	72,176	6.80	19.73	34.54	4.80	-0.06	0.10	7	1.00	Directed	Unipartite	word normed set_size frequency concreteness homograph part_of_speech mean_connectivity resonance_probability resonance_strength use_code	group_size n_responses fsg bsg msg osg n_mediators n_mediators_unnormed n_overlaps n_overlaps_unnormed	683 KiB	1.2 MiB	1.1 MiB	1.0 MiB