LING1109 - module key concepts wk 4-5 Flashcards

1
Q

Corpus linguistics brings a set..

A

of methods to the empirical study of language

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2
Q

Corpus linguists work with…

A

datasets too large to be read and analysed by individual researchers

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3
Q

Corpus linguistics uses techniques like…

A

frequency lists and concordance lines to study study patterns in corpora

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4
Q

A corpus is best used

A

to answer a research question it was designed to answer

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5
Q

Corpora can be

A

written, spoken or signed

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6
Q

The “corpus driven” approach examines..

A

what is frequent or salient in the data

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7
Q

The “corpus based” approaches..

A

involves bring a hypothesis to the data and testing it out.

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8
Q

Monitor corpora develops

A

dataset that grows over time and that contains a variety of materials

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9
Q

Sample corpora seek to

A

represent a particular type of language over a specific period of time

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10
Q

Corpus linguists use..

A

transparent, replicable methods, to avoid selecting only examples from their data that support their hypothesis

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11
Q

Corpora can be

A

monolingual, bilingual or multilingual

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12
Q

A parallel corpus contains..

A

texts in a native language (L1), and their translations (L2)

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13
Q

A comparable corpus

A

is a corpus based on the same sampling frame as another corpus

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14
Q

Corpus linguistics uses large collections of..

A

machine readable texts to search for patterns in discourse

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15
Q

Collocates are words

A

that typically accompany a “node” word (that is the word that you are interested in studying)

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16
Q

“Token” is used to refer

A

to overall frequency of lexical items; “type” means the different words that turn up in corpus

17
Q

“Salience”

A

refers to how strongly connected a word is to another word, and can be measured in various ways

18
Q

Individual collocates can be grouped into..

A

a set of related lexical items in an identified topic area or category established by the analyst

19
Q

“Lexical richness” means..

A

there are a lot of different words in the same topic area, measurable by overall frequency of tokens in the category, or proportion of tokens in a category