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Computational and Corpus-Based Phraseology

Overview of attention for book
Cover of 'Computational and Corpus-Based Phraseology'

Table of Contents

  1. Altmetric Badge
    Book Overview
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    Chapter 1 The Grammatical Environment of Intensifier-Noun Collocations: Insights from Lexical Priming Theory
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    Chapter 2 Towards a Typology of Microsyntactic Constructions
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    Chapter 3 ‘Alla finfine sono daccordo’: A Corpus-Based Case Study on Italian Adverbial Phrases Grammaticalization
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    Chapter 4 On the Structural Disambiguation of Multi-word Terms
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    Chapter 5 Phraseology in Specialised Language: A Contrastive Analysis of Mitigation in Academic Papers
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    Chapter 6 “Sword” Metaphors in Nikita Khrushchev’s Political Rhetoric
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    Chapter 7 Multiword Units and N-Grams Naming FEAR in the Israel-Corpus
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    Chapter 8 Slovene Multi-word Units: Identification, Categorization, and Representation
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    Chapter 9 Weighted Compositional Vectors for Translating Collocations Using Monolingual Corpora
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    Chapter 10 Phraseological Variation in Spanish Academic Writing
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    Chapter 11 Identifying Lexical Bundles for an Academic Writing Assistant in Spanish
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    Chapter 12 Do Online Resources Give Satisfactory Answers to Questions About Meaning and Phraseology?
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    Chapter 13 Translating Manipulated Idioms (EN>ES) in the Word Sketch Scenario
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    Chapter 14 Nominal Collocations in Scientific English: A Frame-Semantic Approach
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    Chapter 15 Effects of Statistical Learning Ability on the Second Language Processing of Multiword Sequences
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    Chapter 16 Converse Phrasemes and Collocations in Czech: The Case of dát ‘give’ and dostat ‘receive’
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    Chapter 17 Automatic Identification of Academic Phrases for Czech
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    Chapter 18 Translation Correspondences of Digressive Discourse Markers in English and Spanish: A Corpus-Based Study
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    Chapter 19 Context-Induced Reinterpretation of Phraseological Verbs
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    Chapter 20 Adjectivation of Attributive Nouns in French and Spanish: A Corpus-Based Study of NOUN+clé/clave and NOUN+éclair/relámpago Expressions
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    Chapter 21 MBLA Social Corpus
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    Chapter 22 A Cognitive Modeling Approach on Ironical Phraseology in Twitter
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    Chapter 23 Profiling Idioms:
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    Chapter 24 Typical Phraseological Units in Poetic Texts
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    Chapter 25 Semantic Prosody in Middle Construction Predicates: Exploring Adverb + Verb Collocation in Middles
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    Chapter 26 Classification of the Combinatorial Behavior of Verbs in the Marketing Domain
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    Chapter 27 “You Took the Word Out of My Mouth”: A Morphosyntactic and Semantic Analysis of a Phraseological Lexicon of Colombian Spanish
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    Chapter 28 Translating Emotional Phraseology: A Case Study
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    Chapter 29 The Difficult Identification of Multiworld Expressions: From Decision Criteria to Annotated Corpora
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    Chapter 30 The Portrait of Dorian Gray: A Corpus-Based Analysis of Translated Verb + Noun (Object) Collocations in Peninsular and Colombian Spanish
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    Chapter 31 Phraseological Sequences Ending in of in L2 Novice Academic Writing
Overall attention for this book and its chapters
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (67th percentile)
  • Average Attention Score compared to outputs of the same age and source

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Title
Computational and Corpus-Based Phraseology
Published by
Lecture notes in computer science, January 2019
DOI 10.1007/978-3-030-30135-4
ISBNs
978-3-03-030134-7, 978-3-03-030135-4
Editors

Gloria Corpas Pastor, Ruslan Mitkov

X Demographics

X Demographics

The data shown below were collected from the profiles of 7 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 7 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 7 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 3 43%
Student > Bachelor 2 29%
Student > Ph. D. Student 1 14%
Professor > Associate Professor 1 14%
Readers by discipline Count As %
Linguistics 5 71%
Arts and Humanities 1 14%
Computer Science 1 14%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 5. 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 25 September 2019.
All research outputs
#6,975,487
of 23,577,654 outputs
Outputs from Lecture notes in computer science
#2,210
of 8,151 outputs
Outputs of similar age
#140,789
of 440,888 outputs
Outputs of similar age from Lecture notes in computer science
#8
of 16 outputs
Altmetric has tracked 23,577,654 research outputs across all sources so far. This one has received more attention than most of these and is in the 70th percentile.
So far Altmetric has tracked 8,151 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.1. This one has gotten more attention than average, scoring higher than 72% 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 440,888 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 67% of its contemporaries.
We're also able to compare this research output to 16 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 50% of its contemporaries.