Data

A large dataset of timed sensibility judgments for existing and novel compounds

This dataset contains data from a large study in which participants had to decide whether word combinations such as airport and wormgrade have a sensible interpretation. The dataset is analysed in some of my empirical studies, and is published via the Open Science Framework:

Link to data: https://osf.io/7kynq/

Data and scripts from publications

Here you can find datasets (usually accompanied by analysis scripts) for my empirical studies:

• Gatti, D., Günther, F., & Rinaldi, L. (2023). Valence without meaning: Investigating form and semantic components in pseudowords valence. psyArXiv preprint, https://psyarxiv.com/sfzgr/ 

Link to data: https://osf.io/kv9at/ 

• Gatti, D., Günther, F., & Rinaldi, L. (2023). A body map beyond perceptual experience. psyArXiv preprint, https://psyarxiv.com/mt3rh

Link to data: https://osf.io/dnt2p  

• Günther, F., Marelli, M., Tureski, S., & Petilli, M. A. (2023). ViSpa (Vision Spaces): A computer-vision-based representation system for individual images and concept prototypes, with large-scale evaluation. Psychological Review, 130, 896-934. 

Link to data: https://doi.org/10.17605/OSF.IO/QVW9C   

• Petilli, M. A., Günther, F., & Marelli, M. (2022). The Flickr frequency norms: what 17 years of images tagged online tell us about lexical processing. Behavior Research Methods. Advance online publication. 

Link to data: https://osf.io/2zfs3/   

• Günther, F., & Rinaldi, L. (2022). Language statistics as a window into mental representations. Scientific Reports, 12, 8043. 

Link to data: https://doi.org/10.17605/OSF.IO/6ZK8S 

• Günther, F., & Marelli, M. (2022). Patterns in CAOSS: Distributed representations predict variation in relational interpretations for familiar and novel compound words.Cognitive Psychology, 134, 101471. 

Link to data: https://doi.org/10.17605/OSF.IO/YCD64

• Günther, F., Press, S. A., Dudschig, C., & Kaup, B. (2022). The limits of automatic sensorimotor processing during word processing: Investigations with repeated linguistic experience, memory consolidation during sleep, and rich linguistic learning contexts. Psychological Research, 86, 1792-1803.

Link to data: https://doi.org/10.17605/OSF.IO/VXRHN 

• Petilli, M. A., Günther, F., Vergallito, A., Ciapparelli, M., & Marelli, M. (2021). Data-driven computational models reveal perceptual simulation in word processing. Journal of Memory and Language, 117, 104194.  

Link to data: https://osf.io/n7gqa/ 

• Günther, F., & Marelli, M. (2021). CAOSS and Transcendence: Modeling role-dependent constituent meanings in compounds. Morphology, Advance online publication.

Link to data: https://doi.org/10.17605/OSF.IO/JXYRN 

• Gupta, A., Günther, F., Plag, I., Kallmeyer, L., & Conrad, S. (2021). Combining text and vision in compound semantics: Towards a cognitively plausible multimodal model. In K. Evang, L. Kallmeyer, R. Osswald, J. Waszczuk, & T. Zesch (Eds.), Proceedings of the 17th Conference on Natural Language Processing (KONVENS 2021) (p. 218-222). Düsseldorf, Germany: KONVENS 2021 Organizers. 

Link to data: https://doi.org/10.17026/dans-xdp-3qhj 

• Günther, F., Petilli, M. A., Vergallito, A. & Marelli, M. (2020). Images of the unseen: Extrapolating visual representations for abstract and concrete words in a data-driven computational model. Psychological Research, Advance online publication. 

Link to data: https://doi.org/10.17605/OSF.IO/45HDZ

• Günther, F., Nguyen, T., Chen, L., Dudschig, C., Kaup, B., & Glenberg, A. M. (2020). Immediate sensorimotor grounding of novel concepts learned from language alone. Journal of Memory and Language, 115, 104172.

Link to data: https://doi.org/10.17605/OSF.IO/FTXJY

• Günther, F., Petilli, M. A., & Marelli, M. (2020). Semantic transparency is not invisibility: A computational model for perceptually-grounded conceptual combination in word processing. Journal of Memory and Language, 112, 104104.

Link to data: https://doi.org/10.17605/OSF.IO/KMRV7

• Günther, F., & Marelli, M. (2020). Trying to make it work: Compositional effects in the processing of compound "nonwords". Quarterly Journal of Experimental Psychology, 73, 1082-1091.

Link to data: https://doi.org/10.6084/m9.figshare.7867772.v1                   

• Günther, F., Marelli, M., & Bölte, J. (2020). Semantic transparency effects in German compounds: A large dataset and multiple-task investigation. Behavior Research Methods, 52, 1208-1224.

Link to data: https://doi.org/10.6084/m9.figshare.8295101

• Günther, F., Smolka, E., & Marelli, M. (2019). 'Understanding' differs between English and German: Capturing Systematic Language Differences of Complex Words. Cortex, 116, 168-175.

Link to data: https://doi.org/10.1016/j.cortex.2018.09.007

• Günther, F., & Marelli, M. (2019). Enter sand-man: Compound processing and semantic transparency in a compositional perspective. Journal of Experimental Psychology: Learning, Memory, and Cognition, 45, 1872-1882.

Link to data: http://dx.doi.org/10.1037/xlm0000677.supp

• Günther, F., & Marelli, M. (2018). The language-invariant aspect of compounding: Predicting compound meanings across languages. In E. Cabrio, A. Mazzei, & F. Tamburini (Eds.), Proceedings of the Fifth Italian Conference on Computational Linguistics (pp. 230-234). Turin, Italy: Accademia University Press.

Link to data: http://doi.org/10.17605/OSF.IO/KMYH8 

• Günther, F., Dudschig, C., & Kaup, B. (2018). Symbol grounding without direct experience: Do words inherit sensorimotor activation from purely linguistic context? Cognitive Science, 42, 336-374.   

Link to data: https://doi.org/10.6084/m9.figshare.5357470.v1

• Günther, F., & Marelli, M. (2016). Understanding Karma Police: The Perceived Plausibility of Noun Compounds as Predicted by Distributional Models of Semantic Representation. PLoS ONE, 11 (10), e0163200.

Link to data: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0163200#sec043

• Günther, F., Dudschig, C., & Kaup, B. (2016). Predicting lexical priming effects from distributional semantic similarities: A replication with extension. Frontiers in Psychology, 7, 1646.          

Link to data: https://doi.org/10.6084/m9.figshare.4057695.v1

• Günther, F., Dudschig, C., & Kaup, B. (2016). Latent Semantic Analysis cosines as a cognitive similarity measure: Evidence from priming studies. Quarterly Journal of Experimental Psychology, 69, 626-653.        

Link to data: https://doi.org/10.6084/m9.figshare.4056513.v1