The word association norms for Slovenian SWOW-SL 1.0 contain words and their associations collected in the scope of the project "Mali svet besed" or Small World of Words. SWOW-SL 1.0 contains free word associations for 1,000 different cues in Slovenian collected up to November 5, 2024. It includes all 19,898 responses collected online from more than 1,100 native Slovenian speakers, each providing up to 3 associations per given cue. The word association norms - the associative frequency and associative strength - comprise more than 37,000 unique cue-association pairs.

The file SWOW-SL1.0_responses.tsv contains all collected responses, which are provided both in their original form and in two normalized forms (word-lemmatized, normalized). SWOW-SL1.0_participants.tsv contains participant metadata collected in the experiment, such as age and education. The file SWOW-SL1.0_statistics_normalized.tsv provides the aggregated word association norms, i.e., frequency statistics of all cue-association pairs on normalized responses, while SWOW-SL1.0_statistics_raw.tsv is based on raw, unprocessed responses. Additional information about the data and processing is provided in README.txt.

 SWOW-SL1.0.zip [1.3Mb]

Citation: Brglez, Mojca; Vintar, Špela and De Deyne, Simon, 2024, Word association norms for Slovenian SWOW-SL 1.0, Slovenian language resource repository CLARIN.SI, ISSN 2820-4042, http://hdl.handle.net/11356/1980.

Three-response associations were collected from 2016 to 2023 for 10,000 cue words, each answered by about 76 participants on average. Participants were native speakers in Mandarin Chinese or other Chinese dialects. A dataset before word and participant cleaning is provided, where 85 taboo words in responses were masked, and 19 taboo words in cue words were deleted. Preprocessing ended up including 55 participants for each cue word. A dataset after preprocessing is provided, containing responses for 10,024 cue words contributed by 30,504 participants, for a total of 551,320 trials. Each row of datasets is a single trial, consisting of demographic information from one participant, and his or her three responses for one cue word. Scripts in MATLAB for preprocessing can be found on the SWOW-ZH GitHub page https://github.com/lib314a/SWOWZH and the raw and preprocessed data, cue and response statistics, and centrality measures can be found below:

 SWOW-ZH23 [49Mb]

We also provide relatedness measures for word pairs based on cosine similarity for associative strength distributions, pointwise mutual information weighted distribution (PPMI), random walk vectors (RW) and compressed random walk vectors. Note that files contain pairwise entries on each row and are xz compressed to reduce file size.

 SWOW-ZH23 Relatedness measures (R1) [321Mb]
 SWOW-ZH23 Relatedness measures (R123) [395Mb]

Citation: Li, B., Ding, Z., De Deyne, S., & Cai, Q. (2024). A large-scale database of Mandarin Chinese word associations from the Small World of Words project. Behavior Research, 57, 34 (2025). https://doi.org/10.3758/s13428-024-02513-1.

Rioplatense is a Spanish variant spoken in South America, primarily in Uruguay and Argentina. The following dataset is currently under review and is likely to be subject to minor updates (e.g., spellchecks).
Here we release the full raw data of the SWOW-RP project as well as a balanced preprocessed dataset where each cue is judged by exactly 70 participants and responses are normalized and spellchecked. Scripts for preprocessing and evaluation can be found at https://github.com/almadana/SWOW-RP. Raw and processed data, together with cue and response statistics can be found below.

 SWOW-RP22 [79Mb]

Citation: Cabana, A., Zugarramurdi, C., Valle-Lisboa, J.C., & De Deyne, S. (2024). The “Small World of Words” free association norms for Rioplatense Spanish. Behavior Research Methods, 56 (2), 968-985.

Word association and participant data for 100 primary, secondary and tertiary responses to 12,292 cues. The data published in Behavior Research Methods were collected between 2011 and 2018. The preprocessed data consist of normalizations of cues and responses by spell-checking them, correcting capitalization and Americanizing. In addition to normalizing cues and responses, the preprocessed file contains data in which each cue is judged by exactly 100 participants (see GitHub repository for details).

Scripts with a processing pipeline to analyse these data in R can be obtained from the SWOWEN-2018 GitHub repository. Note to R users: use the following command to deal with quotation, otherwise the entire file might not be read in correctly. X= read_delim('strength.SWOW-EN.R123.csv',delim='\t',quote = '',escape_backslash = F,escape_double = F) Raw and processed data, together with cue and response statistics can be found below.

 SWOW-EN18 [80Mb]

Dutch word association data (SWOW-NL). Word association and participant data for 100 primary, secondary and tertiary responses to 12,571 cues as reported in De Deyne, Navarro and Storms (2013).

 Associative strength [22Mb]
  Matlab .mat file [10Mb]