1. Mike Scott Aston University INWWCT, Trondheim October 3rd, 2011
Networks of Key Words
Mike Scott
Aston University
INWWCT, Trondheim
October 3rd, 2011

2. Abstract
The notion of keyness is important for document retrieval, for language learning and for study of the nature of text. Keyness, a textual not a linguistic quality, may be shared by certain words and phrases in one text, but its patterning is further distributed across text sets of various dimensions in associates (Scott, 1997) and clustering. This presentation considers the network patterns of keyness which can be investigated using quite simple software procedures and the extent to which these patternings may relate to a user’s needs and interests.
Scott, M., 1997, "PC Analysis of Key Words -- and Key Key Words", System, Vol. 25, No. 1, pp

5. Key words (KWs) Issues Keyness Aboutness Distribution patterns of KWs
… in texts and across corpora

6. complex pattern

7. or simple

8. fractal?

9. A fractal is "a rough or fragmented geometric shape that can be split into parts, each of which is (at least approximately) a reduced-size copy of the whole,"[1] a property called self-similarity
(Wikipedia)
[1] Mandelbrot, B.B. (1982). The Fractal Geometry of Nature. W.H. Freeman and Company.
Fractal

11. aboutness
importance
a textual category
Keyness

12. KWs

13. frequencies

14. aboutness what the text is about what the message is what it all means
picture from mindreadersdictionary.com

15. importance
centrality

16. PC Identification of KWs
simple verbatim repetition
no allowance for anaphora, synonymy, antonymy etc.
simple frequency threshold
one word, or more than one?

17. Corpus-based or corpus-driven?
Machine-identified keyness is ideal for corpus-driven research
The researcher lets the PC suggest areas needing further chasing up
See recent work by McEnery, Baker, etc.
Corpus-based or corpus-driven?

18. Dispersion within the text

19. Global KWs

20. Local KWs

21. middling burstiness verbs appears begins puts observes replies
continues
says
considers
etc.

22. Distribution patterns across the corpus

23. Key Key Words
A "key key-word" is one which is "key" in more than one of a number of related texts.
The more texts it is "key" in, the more "key key" it is.

24. Associates
An "associate" of key-word X is another key-word (Y) which co-occurs with X in a number of texts.
(It may or may not co-occur in proximity to key-word X.)
Association strength measured using a standard collocation statistic, here MI3

25. Climate change LexisNexis database 9,444 stories UK press 2010

26. KKWs

27. Associates

28. waste

29. university

30. Conclusions but early days, lots of questions:
KW patterns within individual texts
within the corpus or sub-corpus
but early days, lots of questions:
are any KW patternings fractal?
do specialised corpora have specialised KKWs?