Senior Lecturer at the University of Birmingham studying language, perception and multimodal communication using data-science-driven linguistics. General Editor at Language & Cognition. Author of "Statistics for Linguists: An introduction Using R".
This paper investigates gesture as a resource for marking politeness-related meanings. We asked 1... more This paper investigates gesture as a resource for marking politeness-related meanings. We asked 14 Korean and 14 Catalan participants to retell a cartoon, once to an unknown superior and once to a close friend. Participants in both languages curtail gestures when interacting with a socially distant superior. Speakers of both languages produced fewer gestures when addressing the superior, reduced their gesture space, decreased the encoding of manner, and reduced the use of character-viewpoint gestures. We see the decrease in gesture frequency and the less frequent encoding of manner as indicators of lower levels of iconicity when talking with status superiors. Curtailing gesture marks a less playful communicative context, and a more serious and deferential persona. Altogether, our research speaks to the importance of politeness in gesture production, and the social nature of gestures in human communication.
This paper reviews recent research using participant ratings to measure the iconicity (form-meani... more This paper reviews recent research using participant ratings to measure the iconicity (form-meaning resemblance) of words and signs. This method, by enabling wide coverage of lexical items and cross-linguistic comparison, has revealed systematic patterns in how iconicity is distributed across the vocabularies of different languages. These findings are consistent with established linguistic and psychological theory on iconicity, and they connect iconicity to factors like learning and acquisition, semantics, pragmatic aspects of language like playfulness, and to the semantic neighborhood density of words and signs. After taking stock of this research, we look critically at the construct validity of iconicity ratings, considering an alternative account of iconicity ratings recently put forward by Thompson, Arthur Lewis, Kimi Akita & Youngah Do. 2020a. Iconicity ratings across the Japanese lexicon: A comparative study with English. Linguistics Vanguard 6. 20190088. They propose that, for most vocabulary, participants might rate the iconicity of different words based on their meaning alone – specifically the degree to which it relates to the senses – independently of actual form-meaning resemblance. We argue that their hypothesis cannot account for many of the various, theory-driven results from this line of research, which strongly support the conclusion that the ratings really do measure iconicity.
We have evolved to become who we are, at least in part, due to our general drive to create new th... more We have evolved to become who we are, at least in part, due to our general drive to create new things and ideas. When seeking to improve our creations, ideas, or situations, we systematically overlook opportunities to perform subtractive changes. For example, when tasked with giving feedback on an academic paper, reviewers will tend to suggest additional explanations and analyses rather than delete existing ones. Here, we show that this addition bias is systematically reflected in English language statistics along several distinct dimensions. First, we show that words associated with an increase in quantity or number (e.g., add, addition, more, most) are more frequent than words associated with a decrease in quantity or number (e.g., subtract, subtraction, less, least). Second, we show that in binomial expressions, addition‐related words are mentioned first, that is, add and subtract rather than subtract and add. Third, we show that the distributional semantics of verbs of change, such as to improve and to transform, overlap more with the distributional semantics of add/increase than subtract/decrease, which suggests that change verbs are implicitly biased toward addition. Fourth, addition‐related words have more positive connotations than subtraction‐related words. Fifth, we demonstrate that state‐of‐the‐art large language models, such as the Generative Pre‐trained Transformer (GPT‐3), are also biased toward addition. We discuss the implications of our results for research on cognitive biases and decision‐making.
This paper investigates gesture as a resource for marking politeness-related meanings. We asked 1... more This paper investigates gesture as a resource for marking politeness-related meanings. We asked 14 Korean and 14 Catalan participants to retell a cartoon, once to an unknown superior and once to a close friend. Participants in both languages curtail gestures when interacting with a socially distant superior. Speakers of both languages produced fewer gestures when addressing the superior, reduced their gesture space, decreased the encoding of manner, and reduced the use of character-viewpoint gestures. We see the decrease in gesture frequency and the less frequent encoding of manner as indicators of lower levels of iconicity when talking with status superiors. Curtailing gesture marks a less playful communicative context, and a more serious and deferential persona. Altogether, our research speaks to the importance of politeness in gesture production, and the social nature of gestures in human communication.
This paper reviews recent research using participant ratings to measure the iconicity (form-meani... more This paper reviews recent research using participant ratings to measure the iconicity (form-meaning resemblance) of words and signs. This method, by enabling wide coverage of lexical items and cross-linguistic comparison, has revealed systematic patterns in how iconicity is distributed across the vocabularies of different languages. These findings are consistent with established linguistic and psychological theory on iconicity, and they connect iconicity to factors like learning and acquisition, semantics, pragmatic aspects of language like playfulness, and to the semantic neighborhood density of words and signs. After taking stock of this research, we look critically at the construct validity of iconicity ratings, considering an alternative account of iconicity ratings recently put forward by Thompson, Arthur Lewis, Kimi Akita & Youngah Do. 2020a. Iconicity ratings across the Japanese lexicon: A comparative study with English. Linguistics Vanguard 6. 20190088. They propose that, for most vocabulary, participants might rate the iconicity of different words based on their meaning alone – specifically the degree to which it relates to the senses – independently of actual form-meaning resemblance. We argue that their hypothesis cannot account for many of the various, theory-driven results from this line of research, which strongly support the conclusion that the ratings really do measure iconicity.
We have evolved to become who we are, at least in part, due to our general drive to create new th... more We have evolved to become who we are, at least in part, due to our general drive to create new things and ideas. When seeking to improve our creations, ideas, or situations, we systematically overlook opportunities to perform subtractive changes. For example, when tasked with giving feedback on an academic paper, reviewers will tend to suggest additional explanations and analyses rather than delete existing ones. Here, we show that this addition bias is systematically reflected in English language statistics along several distinct dimensions. First, we show that words associated with an increase in quantity or number (e.g., add, addition, more, most) are more frequent than words associated with a decrease in quantity or number (e.g., subtract, subtraction, less, least). Second, we show that in binomial expressions, addition‐related words are mentioned first, that is, add and subtract rather than subtract and add. Third, we show that the distributional semantics of verbs of change, such as to improve and to transform, overlap more with the distributional semantics of add/increase than subtract/decrease, which suggests that change verbs are implicitly biased toward addition. Fourth, addition‐related words have more positive connotations than subtraction‐related words. Fifth, we demonstrate that state‐of‐the‐art large language models, such as the Generative Pre‐trained Transformer (GPT‐3), are also biased toward addition. We discuss the implications of our results for research on cognitive biases and decision‐making.
Uploads
Papers by Bodo Winter