Thoughts on Semantic evolution

An evolutionary reconstruction of meanings of the cognacy tree of Proto-Indo-European *st(e)h₂w-ro- ’big cattle’ (?) (by Harald Hammarström) An evolutionary reconstruction of meanings of the cognacy tree of Proto-Indo-European *st(e)h₂w-ro- ’big cattle’ (?) (by Harald Hammarström)
I have not shared anything in a month, since I have been on a 'road-trip', first to Arizona for the CES conference, and then to Beijing and Changsha (Hunan Province) for a lecture series on historical and evolutionary linguistics.
In Arizona, we (with Harald Hammarström and Sandra Cronhamn) presented some results of evolutionary semantic studies on culture vocabularies of our corpus, including data from Indo-European, Caucasian families, Turkic, Uralic, Basque and ancient Semitic (book of abstracts is found here). This study has two aspects: one being the causalities of change rates, the second directionality of semantic change.
In this post, I will focus on the first aspect, causalities of change rates. As our data, we used the 100-list of cultural words of farming, pastoralism, hunting, war, technology, and industry, that we have in our database DiACL. We built an evolutionary model, where we measured gain and loss rates of 21,874 meaning tokens (6,224 types) within cognate trees, contrasted against Glottolog reference trees. After adjustment for transition frequency, 3,442 meanings remained. The gain and loss rates (given as probabilites) we tested against various metrics. We had some preliminary results, but the issue is still being researched. Previous research on lexical change rates (e.g., Pagel et al, Nature 449, Vejdemo et al, PLOS 2016 11,1) have indicated a connection to word frequency (the more frequent a word is, the lower change rates), as well as to age of acquisition, synonyms, arousal, imageability and average mutual information. However, this research has been performed on basic vocabulary only, and we expect most of these causalities to be less relevant to a vocabulary such as ours. Frequency, for instance, showed no correlation at all to our results. However, we found a negative correlation to borrowability, which is highly noteworthy: apparently, lexemes that are frequently borrowed have slower change rates. Further, we found a correlation to colexifcation tendency, as well as cognacy productivity, which is to be expected (words that change their meaning often and which are diverse in geography are expected to have high change rates). Currently, we test various semantic properties of the lexemes, and this is where the interesting part begins: it is evident that inherent properties that are said to impact gender and classifiers, such as animacy, shape, mass/count etc, have no correlation to change rates. But, cultural aspects, such as labour intensity, processability, possibility to control and change, do have an impact. I am still testing various properties and aspects, and hopefully, results can soon be made ready for submission.   

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