Ch. 10 | Exercise 3

# Chapter 10 | Exercise 3

Consider the frequencies of selected collexemes of GO + ADJ construction in COCA, given in Table 10.1.

Table 10.1. Some adjectives that fill in the slot in the GO + ADJ construction. The data are retrieved automatically as the bigram go (lemma) + any adjective found in COCA
Adjective Frequency in go + ADJ Cx Total frequency in the corpus
haywire 226 297
hog-wild 12 19
batty 17 215
crazy 1821 24804
sick 5 24764
wrong 884 77845
stir-crazy 14 29
unpunished 182 259
blank 326 8478
undetected 201 698

The total number of occurrences of the construction is 28636. Find out which of the adjectives have high Attraction towards the construction and which ones have high Reliance. Make a plot with adjectives as text labels, with the horizontal axis showing the Attraction scores and the vertical axis displaying the Reliance scores.

First, create two vectors: `a`, with the frequencies of the adjectives in the GO + ADJ construction, and `total`, with the total frequencies of the adjectives in the corpus:

```> a <- c(226, 12, 17, 1821, 5, 884, 14, 182, 326, 201) > total <- c(297, 19, 215, 24804, 24764, 77845, 29, 259, 8478, 698) ```

Next, compute the attraction and reliance scores and combine them as columns in a data frame:

```> attr <- 100*a/28636 > rel <- 100*a/total > go <- cbind(attr, rel) ```

Create a character vector with the adjectives and use them as the row names of the data frame:

```> adj <- c('haywire', 'hog-wild', 'batty', 'crazy', 'sick', 'wrong', 'stir-crazy', 'unpunished', 'blank', 'undetected') > rownames(go) <- adj > go [output omitted] ```

The highest Attraction scores belong to crazy (6.36), wrong (3.09) and blank (1.14). The highest Reliance scores are observed for haywire (76.09), unpunished (70.27) and hog-wild (63.16).

To make a plot based on the Attraction and Reliance scores, you can use the following code:

```> plot(attr, rel, type = "n") > text(attr, rel, adj) ```