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New paper on with -ity and -ness out.
What is it about? In a nutshell: What determines the choice of ity/ness
for a given adjective? And do the two affixes contribute the same
meaning? (1/9)

We know that there are clear preferences, in both directions: some
adjectives, for example color adjectives, only take -ness. Others,
often originally from Romance languages, prefer -ity. (2/9)

However, there are also some doublets, and sometimes they seem quite interchangeable, othertimes not so much. (3/9)

I use distributional semantics to address both questions, taking a closer look at the distributional vectors of adjectives and their -ity or -ness derivatives. I look at both adjectives that only occur with either -ity or -ness as well as doublets (4/9)

Striking result for adjectives that take only either affix:
The distributional vectors of the adjectives form rough clusters in line with their affix-preference. In line with these two clusters, the vectors can be successfully used to predict the affix preference. (5/9)

Striking result for the doublets: there is no systematic relationship between the matching derivatives, distributional similarity accross the pairs ranging from very high to very low. (6/9)

The interpretation of the data with regard to whether the two affixes contribute the same meaning is a little more complex. My data only allows me to conclude that the assumption of one single meaning change consistently induced by either affix does not seem justified :) (7/9)

For the analytical pipeline and the vectors and R/Python scripts used, see here (9/9):
doi.org/10.6084/m9.figshare.23

figshareA distributional semantics analysis of the two English suffixes -ity and -nessThis repository contains data and the scripts used for the following paper:Schäfer, M. (accepted with minor revisions). The role of meaning in the rivalry of -ity and -ness: evidence from distributional semantics. [to be published in English Language and Linguistics]Python scripts are used for all distributional semantics analyses, including the t-SNE dimension reduction and subsequent visualization and LDA. R scripts are used for further statistical analyses and figures. More information on the files is provided in the README file.The scripts build on the ukWaC corpus (see Baroni et al. 2009) and the pretrained vectorspaces published with Mikolov et al. (2017), see the links below.Required corpus [Links last checked 2024-07-16]ukWaC: https://wacky.sslmit.unibo.it/doku.php?id=corporaRequired pretrained vectorspaces [Links last checked 2024-07-16]:fasttext vectorspace without subword information:File "wiki-news-300d-1M.vec.zip" fromhttps://fasttext.cc/docs/en/english-vectors.htmlReferencesBaroni, M. & S. Bernardini & A. Ferraresi & E. Zanchetta. 2009. The WaCky Wide Web: A Collection of Very Large Linguistically Processed Web-Crawled Corpora. Language Resources and Evaluation 43 (3): 209-226.Mikolov, T., E. Grave, P. Bojanowski, C. Puhrsch, and A. Joulin (2017). Advances in pre-training distributed word representations. CoRR abs/1712.09405.

@demeco_project electricity / electricness? No, didn’t think so.

@Virginicus Well, doublets are weird :) And relatively rare, in my dataset I have only 130 doublets, in contrast to 3014 adjectives that occur only with -ity (1343) or only with -ness (1671). And finally, of course I had to check further for "electricness" :). It does not occur in my dataset, but in the Corpus of American English, there is a single hit, see below (with "electricity" ever so slightly more frequent, with 26014 hits :)).