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The extent and degree of utterance-final word lengthening in spontaneous speech from 10 languages
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In: Linguistics Vanguard ; https://hal.univ-lyon2.fr/hal-03167445 ; Linguistics Vanguard, 2021, 7 (1), pp.20190063. ⟨10.1515/lingvan-2019-0063⟩ (2021)
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Finding Concept-specific Biases in Form--Meaning Associations ...
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Finding Concept-specific Biases in Form–Meaning Associations ...
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Finding Concept-specific Biases in Form–Meaning Associations
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In: Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (2021)
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CLDF dataset derived from Wichmann's "Lexicostatistical Dataset of Mixe-Zoquean" from 2006 ...
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CLDF dataset derived from Wichmann's "Lexicostatistical Dataset of Mixe-Zoquean" from 2006 ...
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Finding Concept-specific Biases in Form--Meaning Associations ...
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The extent and degree of utterance-final word lengthening in spontaneous speech from 10 languages
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English colour terms carry gender and valence biases: A corpus study using word embeddings
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In: PLOS ONE, vol. 16, no. 6, pp. e0251559 (2021)
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Abstract:
In Western societies, the stereotype prevails that pink is for girls and blue is for boys. A third possible gendered colour is red. While liked by women, it represents power, stereotypically a masculine characteristic. Empirical studies confirmed such gendered connotations when testing colour-emotion associations or colour preferences in males and females. Furthermore, empirical studies demonstrated that pink is a positive colour, blue is mainly a positive colour, and red is both a positive and a negative colour. Here, we assessed if the same valence and gender connotations appear in widely available written texts (Wikipedia and newswire articles). Using a word embedding method (GloVe), we extracted gender and valence biases for blue, pink, and red, as well as for the remaining basic colour terms from a large English-language corpus containing six billion words. We found and confirmed that pink was biased towards femininity and positivity, and blue was biased towards positivity. We found no strong gender bias for blue, and no strong gender or valence biases for red. For the remaining colour terms, we only found that green, white, and brown were positively biased. Our finding on pink shows that writers of widely available English texts use this colour term to convey femininity. This gendered communication reinforces the notion that results from research studies find their analogue in real word phenomena. Other findings were either consistent or inconsistent with results from research studies. We argue that widely available written texts have biases on their own, because they have been filtered according to context, time, and what is appropriate to be reported.
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Keyword:
artificial intelligence (AI); colour psychology; emotion; GloVe word embeddings; LIWC; natural language processing (NLP)
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URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0251559 https://doi.org/10.1371/journal.pone.0251559 http://nbn-resolving.org/urn/resolver.pl?urn=urn:nbn:ch:serval-BIB_5BF9A24CC7B92 https://serval.unil.ch/notice/serval:BIB_5BF9A24CC7B9 https://serval.unil.ch/resource/serval:BIB_5BF9A24CC7B9.P001/REF.pdf
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CLDF dataset derived from Wichmann et al.'s "ASJP Database" v17 from 2016 ...
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CLDF dataset derived from Wichmann et al.'s "ASJP Database" v18 from 2018 ...
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CLDF dataset derived from Wichmann et al.'s "ASJP Database" v19 from 2020 ...
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CLDF dataset derived from Wichmann et al.'s "ASJP Database" v13 from 2010 ...
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CLDF dataset derived from Wichmann et al.'s "ASJP Database" v15 from 2012 ...
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CLDF dataset derived from Wichmann et al.'s "ASJP Database" v19 from 2020 ...
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CLDF dataset derived from Wichmann et al.'s "ASJP Database" v19 from 2020 ...
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CLDF dataset derived from Wichmann et al.'s "ASJP Database" from 2010 ...
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CLDF dataset derived from Wichmann et al.'s "ASJP Database" v14 from 2011 ...
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CLDF dataset derived from Wichmann et al.'s "ASJP Database" v16 from 2013 ...
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