Predicting concreteness and perceivability

C.W.J. van Miltenburg

Research output: Contribution to ConferenceAbstractOther research output

Abstract

Concreteness ratings are often used as a measure of readability. There have been several attempts to build a model that accurately predicts human judgments of concreteness, but none of them incorporate a measure of sensory perceivability. This is striking because of two reasons: (1) it is a salient aspect of concrete terms that they tend to denote objects that are more directly experienced, (2) recent literature shows that sensory perceivability is a strong predictor of readability.

We created a model to predict concreteness as well as sensory perceivability ratings. We looked at factors common in the literature, and in addition our model is enriched with corpus data indicating:
* The relative frequency of perception related modifiers (e.g. blue, tasty, rough) occurring with each noun. Perception-relatedness was determined using WordNet mappings from the SUMO ontology.
* The relative frequency of kind-level modifiers (e.g. academic, vegetarian, military) occurring with each noun. These modifiers show us that the noun involved is a higher-level noun that can have subclasses. Whether a modifier is a kind-level modifier is determined on the basis of their morphology (ending in –ic, -ary, -ian).

We show the performance of our model on human ratings, and discuss some hidden assumptions behind recent studies. For example: Feng et al.'s (2011) model assumes that concreteness ratings are based on all senses of a word. Is this true, or do participants in concreteness rating studies base their judgments only on the predominant sense?
Original languageEnglish
Publication statusPublished - 2015
EventCLIN 25 -
Duration: 6 Feb 20156 Feb 2015

Conference

ConferenceCLIN 25
Period6/02/156/02/15

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van Miltenburg, C. W. J. (2015). Predicting concreteness and perceivability. Abstract from CLIN 25, .
van Miltenburg, C.W.J. / Predicting concreteness and perceivability. Abstract from CLIN 25, .
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title = "Predicting concreteness and perceivability",
abstract = "Concreteness ratings are often used as a measure of readability. There have been several attempts to build a model that accurately predicts human judgments of concreteness, but none of them incorporate a measure of sensory perceivability. This is striking because of two reasons: (1) it is a salient aspect of concrete terms that they tend to denote objects that are more directly experienced, (2) recent literature shows that sensory perceivability is a strong predictor of readability.We created a model to predict concreteness as well as sensory perceivability ratings. We looked at factors common in the literature, and in addition our model is enriched with corpus data indicating:* The relative frequency of perception related modifiers (e.g. blue, tasty, rough) occurring with each noun. Perception-relatedness was determined using WordNet mappings from the SUMO ontology.* The relative frequency of kind-level modifiers (e.g. academic, vegetarian, military) occurring with each noun. These modifiers show us that the noun involved is a higher-level noun that can have subclasses. Whether a modifier is a kind-level modifier is determined on the basis of their morphology (ending in –ic, -ary, -ian).We show the performance of our model on human ratings, and discuss some hidden assumptions behind recent studies. For example: Feng et al.'s (2011) model assumes that concreteness ratings are based on all senses of a word. Is this true, or do participants in concreteness rating studies base their judgments only on the predominant sense?",
author = "{van Miltenburg}, C.W.J.",
year = "2015",
language = "English",
note = "CLIN 25 ; Conference date: 06-02-2015 Through 06-02-2015",

}

van Miltenburg, CWJ 2015, 'Predicting concreteness and perceivability' CLIN 25, 6/02/15 - 6/02/15, .

Predicting concreteness and perceivability. / van Miltenburg, C.W.J.

2015. Abstract from CLIN 25, .

Research output: Contribution to ConferenceAbstractOther research output

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T1 - Predicting concreteness and perceivability

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PY - 2015

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N2 - Concreteness ratings are often used as a measure of readability. There have been several attempts to build a model that accurately predicts human judgments of concreteness, but none of them incorporate a measure of sensory perceivability. This is striking because of two reasons: (1) it is a salient aspect of concrete terms that they tend to denote objects that are more directly experienced, (2) recent literature shows that sensory perceivability is a strong predictor of readability.We created a model to predict concreteness as well as sensory perceivability ratings. We looked at factors common in the literature, and in addition our model is enriched with corpus data indicating:* The relative frequency of perception related modifiers (e.g. blue, tasty, rough) occurring with each noun. Perception-relatedness was determined using WordNet mappings from the SUMO ontology.* The relative frequency of kind-level modifiers (e.g. academic, vegetarian, military) occurring with each noun. These modifiers show us that the noun involved is a higher-level noun that can have subclasses. Whether a modifier is a kind-level modifier is determined on the basis of their morphology (ending in –ic, -ary, -ian).We show the performance of our model on human ratings, and discuss some hidden assumptions behind recent studies. For example: Feng et al.'s (2011) model assumes that concreteness ratings are based on all senses of a word. Is this true, or do participants in concreteness rating studies base their judgments only on the predominant sense?

AB - Concreteness ratings are often used as a measure of readability. There have been several attempts to build a model that accurately predicts human judgments of concreteness, but none of them incorporate a measure of sensory perceivability. This is striking because of two reasons: (1) it is a salient aspect of concrete terms that they tend to denote objects that are more directly experienced, (2) recent literature shows that sensory perceivability is a strong predictor of readability.We created a model to predict concreteness as well as sensory perceivability ratings. We looked at factors common in the literature, and in addition our model is enriched with corpus data indicating:* The relative frequency of perception related modifiers (e.g. blue, tasty, rough) occurring with each noun. Perception-relatedness was determined using WordNet mappings from the SUMO ontology.* The relative frequency of kind-level modifiers (e.g. academic, vegetarian, military) occurring with each noun. These modifiers show us that the noun involved is a higher-level noun that can have subclasses. Whether a modifier is a kind-level modifier is determined on the basis of their morphology (ending in –ic, -ary, -ian).We show the performance of our model on human ratings, and discuss some hidden assumptions behind recent studies. For example: Feng et al.'s (2011) model assumes that concreteness ratings are based on all senses of a word. Is this true, or do participants in concreteness rating studies base their judgments only on the predominant sense?

M3 - Abstract

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van Miltenburg CWJ. Predicting concreteness and perceivability. 2015. Abstract from CLIN 25, .