How emotion is learned: Semantic learning of novel words in emotional contexts

Snefjella, Bryor; Lana, Nadia; Kuperman, Victor

doi:10.1016/j.jml.2020.104171

Cited by 36 publications

(26 citation statements)

References 98 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…With respect to the second research question, the results of the mixed-effects modeling on the learning outcomes for emotion-laden words revealed that participants in the current study were predicted to recall and retain neutral words better than either positive-or negative-laden items. While this generally supports prior studies in psychology, both with monolingual (e.g., Altarriba & Bauer, 2004;Jay et al, 2008;Snefjella et al, 2020) and bilingual (e.g., Ayçiçegi & Harris, 2004;Ayçiçegi-Dinn & Caldwell-Harris, 2009;Ferré et al, 2010) participants, that mark a contrast between emotion-laden and neutral words, the current study contradicts previous research in psycholinguistics (e.g., Altarriba & Bauer, 2004;Ayçiçegi & Harris, 2004;El-Dakhs & Altarriba, 2019;Kazanas & Altarriba, 2015a, 2015bSnefjella et al, 2020), neurolinguistics (e.g., Hinojosa et al, 2020), and psychology (e.g., Hadley & MacKay, 2006;Jay et al, 2008;MacKay & Ahmetzanov, 2005;MacKay et al, 2004) on learning and memory enhancement. In this research, findings largely show that emotion (e.g., love, hate), emotion-laden (e.g., puppy, jail), and taboo words (e.g., reproductive organs, expletives) are recalled more successfully than neutral words.…”

Section: Learning Expectations For Emotion-laden Vocabularysupporting

confidence: 89%

Emotion-Laden Texts and Words

Driver

2021

Stud Second Lang Acquis

View full text Add to dashboard Cite

This study takes a mixed-methods approach to explore the influence of emotion-laden (positive vs. negative vs. neutral) texts and words on vocabulary learning for Spanish heritage and foreign language learners. Participants (N = 121) were tasked with learning emotion-laden pseudowords embedded in three emotion-laden texts centered around themes of bilingualism, immigration, and identity. Form recognition, translation, and multiple-choice tests were designed to measure vocabulary recall and retention. Results from a mixed-effects modeling analysis showed that the neutral and negative emotion-laden texts predicted better vocabulary learning outcomes than the positive text for both HLLs and FLLs and that neutral words were learned best by all learners. Qualitative findings from open-ended questionnaires suggest emotional arousal as another influential affective factor in vocabulary learning for learners of diverse sociolinguistic backgrounds. Directions for future emotions research in SLA and pedagogical implications of socially relevant, emotion-laden material for vocabulary learning are discussed.

show abstract

Section: Learning Expectations For Emotion-laden Vocabularysupporting

confidence: 89%

Emotion-Laden Texts and Words

Driver

2021

Stud Second Lang Acquis

View full text Add to dashboard Cite

show abstract

“…The findings reviewed above are consistent with the suggestion that distributional models that take only language data as input may be adequate for broadly capturing semantic similarity, and emerging evidence suggests that novel words may, to some degree, acquire embodied representations by virtue of the embodied properties of the contexts in which they appear (Günther et al, 2020;Snefjella et al, 2020; see also Snefjella & Kuperman, 2016). An interesting open question is whether embodied experience alone (e.g., Öttl et al, 2017) also facilitates category learning, or whether language is necessary for carving categorical boundaries into our experience (for review, see Lupyan, 2012).…”

Section: Effects Of Embodied and Distributional Linguistic Informatiosupporting

confidence: 75%

“…Specifically, after novel words were learned in contexts implying upwards or downwards movements, action-congruency effects were found if participants had to access word meaning. This suggests that embodied representations can be acquired via contextual association (see also Snefjella et al, 2020;Snefjella & Kuperman, 2016). However, when people learned similar concepts but were tested for action-congruency effects using a task that did not require accessing the words' meanings (Günther et al, 2018) no action-congruency effects were observed.…”

Section: Effects Of Embodied and Distributional Linguistic Informatiomentioning

confidence: 99%

Building semantic memory from embodied and distributional language experience

Davis

Yee

2021

WIRES Cognitive Science

View full text Add to dashboard Cite

Humans seamlessly make sense of a rapidly changing environment, using a seemingly limitless knowledgebase to recognize and adapt to most situations we encounter. This knowledgebase is called semantic memory. Embodied cognition theories suggest that we represent this knowledge through simulation: understanding the meaning of coffee entails re-instantiating the neural states involved in touching, smelling, seeing, and drinking coffee. Distributional semantic theories suggest that we are sensitive to statistical regularities in natural language, and that a cognitive mechanism picks up on these regularities and transforms them into usable semantic representations reflecting the contextual usage of language. These appear to present contrasting views on semantic memory, but do they? Recent years have seen a push toward combining these approaches under a common framework. These hybrid approaches augment our understanding of semantic memory in important ways, but current versions remain unsatisfactory in part because they treat sensory-perceptual and distributional-linguistic data as interacting but distinct types of data that must be combined. We synthesize several approaches which, taken together, suggest that linguistic and embodied experience should instead be considered as inseparably entangled: just as sensory and perceptual systems are reactivated to understand meaning, so are experience-based representations endemic to linguistic processing; further, sensory-perceptual experience is susceptible to the same distributional principles as language experience. This conclusion produces a characterization of semantic memory that accounts for the interdependencies between linguistic and embodied data 2 that arise across multiple timescales, giving rise to concept representations that reflect our shared and unique experiences.

show abstract

Section: Effects Of Embodied and Distributional Linguistic Information On Semantic Processingsupporting

confidence: 75%

Building semantic memory from embodied and distributional language experience

Davis¹,

Yee²

2021

Preprint

View full text Add to dashboard Cite

Humans seamlessly make sense of a rapidly changing environment, using a seemingly limitless knowledgebase to recognize and adapt to most situations we encounter. This knowledgebase is called semantic memory. Embodied cognition theories suggest that we represent this knowledge through simulation: understanding the meaning of coffee entails re-instantiating the neural states involved in touching, smelling, seeing, and drinking coffee. Distributional semantic theories suggest that we are sensitive to statistical regularities in natural language, and that a cognitive mechanism picks up on these regularities and transforms them into usable semantic representations reflecting the contextual usage of language. These appear to present contrasting views on semantic memory, but do they? Recent years have seen a push toward combining these approaches under a common framework. These hybrid approaches augment our understanding of semantic memory in important ways, but current versions remain unsatisfactory in part because they treat sensory-perceptual and distributional-linguistic data as interacting but distinct types of data that must be combined. We synthesize several approaches which, taken together, suggest that linguistic and embodied experience should instead be considered as inseparably entangled: just as sensory and perceptual systems are reactivated to understand meaning, so are experience-based representations endemic to linguistic processing; further, sensory-perceptual experience is susceptible to the same distributional principles as language experience. This conclusion produces a characterization of semantic memory that accounts for the interdependencies between linguistic and embodied data that arise across multiple timescales, giving rise to concept representations that reflect our shared and unique experiences.

show abstract

How emotion is learned: Semantic learning of novel words in emotional contexts

Cited by 36 publications

References 98 publications

Emotion-Laden Texts and Words

Emotion-Laden Texts and Words

Building semantic memory from embodied and distributional language experience

Building semantic memory from embodied and distributional language experience

Contact Info

Product

Resources

About