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DATA ANALYSIS: LINGUISTICS Analytically speaking...

Felix Grant explores the complexity found within the field of linguistics

arbitrary sign systems with which we attempt to communicate what we seek and find – and scientific computing methods are just as central there as in more physical arenas. At the same time, these qualities of

language have strong practical importance. Language is how we become fully human – whether or not it is an attribute unique to our species, as consensus suggests, it is certainly a powerful component in our dominance. It is how we become socialised and acculturated. It is how some of us make the long climb from newborn tabula rasa to mature professional scientist – encountering, along the way, what Evelyn Rodriguez-Alamo[1]

called ‘the content Haemodynamic response to sound versus silence periods, from Telkemayer et al[3] M 8

y first Damascene vision of what a wonderful tool data analysis can be was not in the physical sciences. In a

holiday homework assignment, when I was 14, a maths teacher asked us to explore, using what he had taught us that term, the suggestion that Shakespeare’s Hamlet might have been written by Marlowe. Two weeks of miscounted words, syllables and parts of speech later, I understood the sheer intellectual thrill of using statistical analysis to explore the unknown. Linguistics is a word used in many ways

by different constituencies, but they have in common the scientific study of (usually, but not always, natural) language. This plurality of meaning makes it representative of language in general. Like all the words which make up natural languages and other means of human-to-human communication

(including, for example, financial currencies) it is, to the exasperational intrigue of science, an ‘arbitrary signifier’. Its meaning lies entirely in the intersecting set of associations between those who transmit and receive it, and is defined by difference from what it is not rather that what it is.

‘Language is how we become fully human – it is how we become socialised and acculturated’

The lure of the unknown is science’s

greatest romantic pull. It can be along the banks of the Amazon or the Congo, it can be on the inaccessible ocean floors or in other galaxies, it can be down in the subatomic or up on the macrocosmic. But it can equally well be in the vast and ever-shifting jungles of


and the vehicles of learning and scientific research for the 21st century’. Analytic approaches to language underpin the effectiveness of learning. Viewed from another perspective, language is how organisations are structured; analysis of effectiveness depends upon linguistic assumptions. As well as being itself an inviting subject for scientific enquiry, then, understanding how language does and doesn’t work is vital to both efficiency and outcomes for every stage and component of the context within which science happens. Computerisation of linguistic data analysis

can be traced back to the 1950s, at least, when computational linguistics was seen as the key to swift translation of technical articles in a rapidly escalating cold war. Linguistic corpus analyses, starting with sorted word frequency lists, were a growth area in 1960s academic application of university computers. Yet, as recently as 1996, a British Academy conference on the influence of information technology on scholarly disciplines included a paper[2]

noting that ‘while IT claims to offer

linguistics an intellectual resource, especially through its methodology, it does not appear to demonstrate its value convincingly to the linguistics community’. How far that last assessment remains true in 2010 is a matter of vigorous debate in some circles; that computerised methods of data analysis are now both widely and productively applied, however, is indisputable. There is a general tendency for such methods to be focused on particular procedural

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