Demonstrative Reference and Semantic Space: A Large-Scale Demonstrative Choice Task Study

被引:9
|
作者
Rocca, Roberta [1 ,2 ,3 ]
Wallentin, Mikkel [1 ,2 ,4 ]
机构
[1] Aarhus Univ, Sch Commun & Culture, Dept Linguist Cognit Sci & Semiot, Aarhus, Denmark
[2] Aarhus Univ, Interacting Minds Ctr, Aarhus, Denmark
[3] Univ Texas Austin, Dept Psychol, Psychoinformat Lab, Austin, TX 78712 USA
[4] Aarhus Univ Hosp, Ctr Funct Integrat Neurosci, Aarhus, Denmark
来源
FRONTIERS IN PSYCHOLOGY | 2020年 / 11卷
基金
欧盟地平线“2020”;
关键词
language; semantics; spatial demonstratives; manipulability; the Demonstrative Choice Task; PERCEPTUAL SPACE; LANGUAGE; WORDS;
D O I
10.3389/fpsyg.2020.00629
中图分类号
B84 [心理学];
学科分类号
04 ; 0402 ;
摘要
Spatial demonstratives (words like this and that) have been thought to primarily be used for carving up space into a peripersonal and extrapersonal domain. However, when given a noun out of context and asked to couple it with a demonstrative, speakers tend to choose this for words denoting manipulable objects (small, harmless, and inanimate), while non-manipulable objects (large, harmful, and animate) are more likely to be coupled with that. Here, we extend these findings using the Demonstrative Choice Task (DCT) procedure and map demonstrative use along a wide spectrum of semantic features. We conducted a large-scale (N = 2197) DCT experiment eliciting demonstratives for 506 words, rated across 65 + 11 perceptually and cognitively relevant semantic dimensions. We replicated the finding that demonstrative choice is influenced by object manipulability. Demonstrative choice was furthermore found to be related to a set of additional semantic factors, including valence, arousal, loudness, motion, time and more generally, the self. Importantly, demonstrative choices were highly structured across participants, as shown by a strong correlation detected in a split-sample comparison of by-word demonstrative choices. We argue that the DCT may be used to map a generalized semantic space anchored in the self of the speaker, the self being an extension of the body beyond physical space into a multidimensional semantic space.
引用
收藏
页数:10
相关论文
共 50 条
  • [1] The semantics of spatial demonstratives in Spanish: a Demonstrative Choice Task study
    Todisco, Emanuela
    Rocca, Roberta
    Wallentin, Mikkel
    [J]. LANGUAGE AND COGNITION, 2021, 13 (04) : 503 - 533
  • [2] A conceptual framework for the study of demonstrative reference
    David Peeters
    Emiel Krahmer
    Alfons Maes
    [J]. Psychonomic Bulletin & Review, 2021, 28 : 409 - 433
  • [3] A conceptual framework for the study of demonstrative reference
    Peeters, David
    Krahmer, Emiel
    Maes, Alfons
    [J]. PSYCHONOMIC BULLETIN & REVIEW, 2021, 28 (02) : 409 - 433
  • [4] Aqueix Caught in the Middle. A Demonstrative Choice Task Study of Catalan Demonstratives
    Todisco, Emanuela
    Rocca, Roberta
    Wallentin, Mikkel
    [J]. PROBUS, 2023, 35 (01) : 31 - 59
  • [5] Against intentionalism: an experimental study on demonstrative reference
    Rostworowski, Wojciech
    Kus, Katarzyna
    Mackiewicz, Bartosz
    [J]. LINGUISTICS AND PHILOSOPHY, 2022, 45 (05) : 1027 - 1061
  • [6] Against intentionalism: an experimental study on demonstrative reference
    Wojciech Rostworowski
    Katarzyna Kuś
    Bartosz Maćkiewicz
    [J]. Linguistics and Philosophy, 2022, 45 : 1027 - 1061
  • [7] Cooperative Multiagent Attentional Communication for Large-Scale Task Space
    Zou, Qijie
    Hu, Youkun
    Yi, Dewei
    Gao, Bing
    Qin, Jing
    [J]. WIRELESS COMMUNICATIONS & MOBILE COMPUTING, 2022, 2022
  • [8] Egocentric and geocentric frames of reference in memory of large-scale space
    McNamara, TP
    Rump, B
    Werner, S
    [J]. PSYCHONOMIC BULLETIN & REVIEW, 2003, 10 (03) : 589 - 595
  • [9] Egocentric and geocentric frames of reference in memory of large-scale space
    Timothy P. McNamara
    Björn Rump
    Steffen Werner
    [J]. Psychonomic Bulletin & Review, 2003, 10 : 589 - 595
  • [10] Leveraging Large-Scale Semantic Networks for Adaptive Robot Task Learning and Execution
    Boteanu, Adrian
    St Clair, Aaron
    Mohseni-Kabir, Anahita
    Saldanha, Carl
    Chernova, Sonia
    [J]. BIG DATA, 2016, 4 (04) : 217 - 235