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Salience and Attention in Surprisal-Based Accounts of Language Processing

Overview of attention for article published in Frontiers in Psychology, June 2016
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Title
Salience and Attention in Surprisal-Based Accounts of Language Processing
Published in
Frontiers in Psychology, June 2016
DOI 10.3389/fpsyg.2016.00844
Pubmed ID
Authors

Alessandra Zarcone, Marten van Schijndel, Jorrig Vogels, Vera Demberg

Abstract

The notion of salience has been singled out as the explanatory factor for a diverse range of linguistic phenomena. In particular, perceptual salience (e.g., visual salience of objects in the world, acoustic prominence of linguistic sounds) and semantic-pragmatic salience (e.g., prominence of recently mentioned or topical referents) have been shown to influence language comprehension and production. A different line of research has sought to account for behavioral correlates of cognitive load during comprehension as well as for certain patterns in language usage using information-theoretic notions, such as surprisal. Surprisal and salience both affect language processing at different levels, but the relationship between the two has not been adequately elucidated, and the question of whether salience can be reduced to surprisal / predictability is still open. Our review identifies two main challenges in addressing this question: terminological inconsistency and lack of integration between high and low levels of representations in salience-based accounts and surprisal-based accounts. We capitalize upon work in visual cognition in order to orient ourselves in surveying the different facets of the notion of salience in linguistics and their relation with models of surprisal. We find that work on salience highlights aspects of linguistic communication that models of surprisal tend to overlook, namely the role of attention and relevance to current goals, and we argue that the Predictive Coding framework provides a unified view which can account for the role played by attention and predictability at different levels of processing and which can clarify the interplay between low and high levels of processes and between predictability-driven expectation and attention-driven focus.

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X Demographics

The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 123 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 4 3%
United States 2 2%
Japan 1 <1%
Finland 1 <1%
Unknown 115 93%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 36 29%
Researcher 17 14%
Student > Doctoral Student 14 11%
Student > Master 11 9%
Professor 10 8%
Other 15 12%
Unknown 20 16%
Readers by discipline Count As %
Linguistics 44 36%
Psychology 25 20%
Neuroscience 8 7%
Computer Science 6 5%
Philosophy 3 2%
Other 7 6%
Unknown 30 24%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 28 May 2020.
All research outputs
#13,980,964
of 22,873,031 outputs
Outputs from Frontiers in Psychology
#14,198
of 29,940 outputs
Outputs of similar age
#186,054
of 340,761 outputs
Outputs of similar age from Frontiers in Psychology
#256
of 430 outputs
Altmetric has tracked 22,873,031 research outputs across all sources so far. This one is in the 37th percentile – i.e., 37% of other outputs scored the same or lower than it.
So far Altmetric has tracked 29,940 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 12.5. This one has gotten more attention than average, scoring higher than 50% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 340,761 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 44th percentile – i.e., 44% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 430 others from the same source and published within six weeks on either side of this one. This one is in the 37th percentile – i.e., 37% of its contemporaries scored the same or lower than it.