The replication crisis: what does it mean for corpus linguistics?


Over the last year, the field of psychology has been rocked by a major public dispute about statistics. This concerns the failure of claims in papers, published in top psychological journals, to replicate.

Replication is a big deal: if you publish a correlation between variable X and variable Y – that there is an increase in the use of the progressive over time, say, and that increase is statistically significant, you expect that this finding would be replicated were the experiment repeated.

I would strongly recommend Andrew Gelman’s brief history of the developing crisis in psychology. It is not necessary to agree with everything he says (personally, I find little to disagree with, although his argument is challenging) to recognise that he describes a serious problem here.

There may be more than one reason why published studies have failed to obtain compatible results on repetition, and so it is worth sifting these out.

In this blog post, what I want to do is try to explore what this replication crisis is – is it one problem, or several? – and then turn to what solutions might be available and what the implications are for corpus linguistics. Continue reading

UCL Summer School in English Corpus Linguistics 2016

I am pleased to announce the fourth annual Summer School in English Corpus Linguistics to be held at University College London from 6-8 July.

The Summer School is a short three-day intensive course aimed at PhD-level students and researchers who wish to get to grips with Corpus Linguistics. Numbers are deliberately limited on a first-come, first-served basis. You will be taught in a small group by a teaching team.

Each day begins with a theory lecture, followed by a guided hands-on workshop with corpora, and a more self-directed and supported practical session in the afternoon.

Aims and objectives of the course

Over the three days, participants will learn about the following:

  • the scope of Corpus Linguistics, and how we can use it to study the English Language;
  • key issues in Corpus Linguistics methodology;
  • how to use corpora to analyse issues in syntax and semantics;
  • basic elements of statistics;
  • how to navigate large and small corpora, particularly ICE-GB and DCPSE.

Learning outcomes

At the end of the course, participants will have:

  • acquired a basic but solid knowledge of the terminology, concepts and methodologies used in English Corpus Linguistics;
  • had practical experience working with two state-of-the-art corpora and a corpus exploration tool (ICECUP);
  • have gained an understanding of the breadth of Corpus Linguistics and the potential application for projects;
  • have learned about the fundamental concepts of inferential statistics and their practical application to Corpus Linguistics.

For more information, including costs, booking information, timetable, see the website.

See also

Impossible logistic multinomials


Recently, a number of linguists have begun to question the wisdom of assuming that linguistic change tends to follow an ‘S-curve’ or more properly, logistic, pattern. For example, Nevalianen (2015) offers a series of empirical observations that show that whereas data sometimes follows a continuous ‘S’, frequently this does not happen. In this short article I try to explain why this result should not be surprising.

The fundamental assumption of logistic regression is that a probability representing a true fraction, or share, of a quantity undergoing a continuous process of change by default follows a logistic pattern. This is a reasonable assumption in certain limited circumstances because an ‘S-curve’ is mathematically analogous to a straight line (cf. Newton’s first law of motion).

Regression is a set of computational methods that attempts to find the closest match between an observed set of data and a function, such as a straight line, a polynomial, a power curve or, in this case, an S-curve. We say that the logistic curve is the underlying model we expect data to be matched against (regressed to). In another post, I comment on the feasibility of employing Wilson score intervals in an efficient logistic regression algorithm.

We have already noted that change is assumed to be continuous, which implies that the input variable (x) is real and linear, such as time (and not e.g. probabilistic). In this post we discuss different outcome variable types. What are the ‘limited circumstances’ in which logistic regression is mathematically coherent?

  • We assume probabilities are free to vary from 0 to 1.
  • The envelope of variation must be constant, i.e. it must always be possible for an observed probability to reach 1.

Taken together this also means that probabilities are Binomial, not multinomial. Let us discuss what this implies. Continue reading

Coping with imperfect data


One of the challenges for corpus linguists is that many of the distinctions that we wish to make are either not annotated in a corpus at all or, if they are represented in the annotation, unreliably annotated. This issue frequently arises in corpora to which an algorithm has been applied, but where the results have not been checked by linguists, a situation which is unavoidable with mega-corpora. However, this is a general problem. We would always recommend that cases be reviewed for accuracy of annotation.

A version of this issue also arises when checking for the possibility of alternation, that is, to ensure that items of Type A can be replaced by Type B items, and vice-versa. An example might be epistemic modal shall vs. will. Most corpora, including richly-annotated corpora such as ICE-GB and DCPSE, do not include modal semantics in their annotation scheme. In such cases the issue is not that the annotation is “imperfect”, rather that our experiment relies on a presumption that the speaker has the choice of either type at any observed point (see Aarts et al. 2013), but that choice is conditioned by the semantic content of the utterance.

Continue reading

Is language really “a set of alternations?”

The perspective that the study of linguistic data should be driven by studies of individual speaker choices has been the subject of attack from a number of linguists.

The first set of objections have come from researchers who have traditionally focused on linguistic variation expressed in terms of rates per word, or per million words.

No such thing as free variation?

As Smith and Leech (2013) put it: “it is commonplace in linguistics that there is no such thing as free variation” and that indeed multiple differing constraints apply to each term. On the basis of this observation they propose an ‘ecological’ approach, although in their paper this approach is not clearly defined.

Continue reading

EDS Resources

This post contains the resources for students taking the UCL English Linguistics MA, all in one place.

Session 15: Introduction to statistics

Sessions 18 and 19: Statistics Workshops

Suggested further reading

Genre differences and experimental observations

Spoken categories, modal verbs and change over time

In a recently-published paper, Bowie, Wallis and Aarts (2013) demonstrate that observations regarding changes in the frequency of modal verbs over time are highly sensitive to differences in genre (‘register’ or ‘text category’). Our paper, although based on spoken British English, may shed some light on a recent dispute between Leech (2011) and Millar (2009) regarding how linguists should interpret corpus observations regarding changes in the modal verb system in written US English.

The following table summarises statistically significant percentage decreases and increases of individual modal verbs as a proportion of the number of tensed verb phrases (VPs that could conceivably take a modal verb), within different spoken genre subcategories of the Diachronic Corpus of Present-day Spoken English (DCPSE). The statistical test used examines differences in observed probabilities between samples, i.e. a Newcombe-Wilson test.

For our purposes the cited percentages do not matter, but the direction of travel (indicated by coloured cells) does.

can may could might shall will should would must All
formal f2f ns ns ns ns ns ns -60% ns -75%
informal f2f 27% -42% ns 47% -32% ns ns ns -53% ns
telephone -37% ns -44% ns -56% -30% ns -44% ns -35%
b. discussions -41% -59% ns ns -83% ns ns ns -54% -20%
b. interviews ns -61% ns -59% ns -41% -55% -32% -57% -35%
commentary ns ns ns ns -93% 58% ns ns -64% ns
parliament ns ns ns ns ns -39% ns -30% ns -20%
legal x-exam 304% ns ns ns ns ns 1,265% 254% ns 157%
spontaneous ns ns ns ns ns ns ns ns ns ns
prepared sp. ns -63% ns ns ns 327% ns -32% -48% ns
All genres ns -40% -11% ns -48% 13% -14% -7% -54% -6%

Significant changes (α<0.05) in the proportion of individual core modals out of tensed verb phrases from the 1960s (LLC) to 1990s (ICE-GB) components in DCPSE, adapted from Bowie et al. 2013.

This study concerns modal verbs within text categories. Against a general baseline (words, verb phrases or tensed verb phrases), the total number of modals decrease in use over the course of the period covered by the data (at least, noting the caveat, for spoken English data sampled comparably). Above, we employ tensed verb phrases as the most meaningful baseline out of the three. See That vexed problem of choice.

  • Note that if we take all genres together (bottom row in the table), except for will, every significant change is a decline in use, but in the (large) category of informal face-to-face conversation (second row from top), can and might are both significantly increasing.
  • Legal cross-examination is a predictable outlier, but broadcast interviews and discussions appear to generate very different results. Continue reading