Just a quick update: the registration for the CL2017 conference at the University of Birmingham (24-28 July) is closing very soon on 30 July. [I shall admit openly that I’m part of the organising committee and therefore advertising it – but genuinely think this conference will be a good one!] This conference series is one of the biggest corpus linguistics events in Europe that runs bi-annually and has been hosted at the universities of Birmingham, Lancaster and Liverpool. The CL2017 programme contains streams related to a variety of CL applications. Of particular interest will be the plenary papers by Susan Conrad, Andrew Hardie, Susan Hunston, Christian Mair, Dan McIntyre and Mike Scott.
I start this post by giving a very quick introduction to concordances. If you are already an experienced corpus linguist, you can skip to the final section on categorising concordance lines. I am curious about your own practices for analysing concordance lines: do you print them out and highlight the different patterns? Or do you annotate the lines electronically, using a concordancer or a spreadsheet? Is there any other option that hasn’t occurred to me yet?
The basic display format in corpus linguistics
In the past year or so I was pre-occupied with relatively abstract, ‘big picture’-style analyses of my corpus (basically key key word and collocation analysis), but now I have come across a theme for which a smaller-scale, qualitative analysis is more appropriate. (Once I’ve wrapped it all up, I hope to share some insights. Or you may have to wait for my thesis to get done …).
For me as a corpus linguist, the go-to tool for any qualitative investigation is the concordancer. As the name suggests, it produces concordances. A concordance is the basic display format in corpus linguistics that lists snippets of the text, illustrating the use of a particular word or phrase in a corpus. Concordance analysis has brought the discipline a long way, especially when Sinclair developed very systematic ways of analysing concordance lines for making dictionaries. (Sinclair’s guidelines are recorded in his book Reading Concordances; it’s a shame that Google Books has no preview …).
For many linguists, searching and concordancing is what they mean by “doing corpus linguistics”.
The way we read concordance lines is quite different from the way we read a text. This vertical reading may take some time getting used to. Here’s an example, concordance lines for language on WebCorp:
You can also use WebCorp to produce concordance lines from the web; or you can access corpora that are available online with integrated concordance functionality, such as the BNCweb or the BYU corpora. (If you want to run concordances on specialised subcorpora on the BYU interface, you might be interested in the slides and the handout from my session at the University of Birmingham Summer School in Corpus Linguistics this year).
Of course, we often want to use corpus linguistic tools on materials that haven’t been made widely available, because it is often necessary to prepare a corpus from scratch for a particular research question. To create concordances for your own texts you using concordancers like AntConc and WordSmith Tools (which you could buy if your institution doesn’t have a license).
What are your personal preferences for analysing concordance lines?
Concordance analysis is all about viewing a word (or phrase) in its co-text to identify any patterns in the way it is used. It’s often helpful to resort the concordance lines. Concordance tools usually let you resort based on the surrounding words (in positions 1-5 or more on the left and right).
[t]his type of manual annotation of concordance lines is often done on concordance printouts with a pen. Software which allows the annotation to be done on the electronic concordance data makes it possible to sort on the basis of the annotations, and to thin the concordance to leave only those lines with or without a certain manual categorisation.
Personally, I usually start with a print out of the simple concordance lines. Then, once I have identified some simple categories I often move on to an Excel spreadsheet. I like being able to add columns for categories (I should just not overdo it, like in the photo…). Moreover, in some versions of Excel, it is possible to select and change the font of particular words in the same cell (seems to work on Excel for Mac but not for Windows). That way, I can highlight the word or phrase which prompts the category for the concordance line. It is also possible to assign a concordance to particular categories.
Some concordancers provide functionality for categorizing concordance lines. In WordSmith Tools it is possible to assign categories (‘sets’). I have only recently tried this function and I’m quite impressed with the range of colours that are available, which you can see in the screenshot on the left. More information is available from the manual. BNCweb also provides a (simple) categorisation function with up to 6 categories. In the example from the screenshot below we would distinguish between can as the modal verb and can as the container for a drink. Of course, the modal is much more frequent (in general language usage, not in a text about coke cans…). Therefore all the example concordance lines represent the modal usage.
I am curious about these features and in how far people use them. If you don’t use these functions, how else do you categorise concordance lines? Do you do it manually, after printing out? In practice, how often do you analyse concordance lines? Are they quite important in your research or do you focus on more quantitative aspects, checking concordance lines when necessary?
Sinclair, J. (2003). Reading Concordances: An Introduction. Harlow: Pearson/Longman.
Wynne, M. (2008). Searching and concordancing. In A. Lüdeling & M. Kytö (Eds.), Corpus Linguistics: An International Handbook (Vol. 1, pp. 706–737). Berlin: Mouton de Gruyter. [pre-publication draft available online]
The full virtual Twitter conversation from throughout the week can be found under the hashtag #ccrss16.
Topics ranged from multiple facets of corpus statistics and their applications in R to Sinclairian lexical items, corpus stylistics and translation studies, specialised corpora and an introduction to Python for corpus linguists. The workshops and talks were held by Johan de Joode, Stefan Evert, Chris Fallaize, Matt Gee, Stefan Th. Gries, Nicholas Groom, Susan Hunston, Andrew Kehoe, Michaela Mahlberg, Lorenzo Mastropierro, Florent Perek, Simon Preston, Pablo Ruano, Adam Schembri, Paul Thompson and I. While most of us are based at UoB, it was great to have colleagues from other institutions and even from abroad join us to share their expertise.
My own session was inspired by a talk from Mark Davies at the ICAME 37 conference (Chinese University of Hong Kong, May 2016), where he demoed the new ‘virtual corpus’ feature on the BYU corpus interface.[Click on the links for the PDF versions of my presentations slides and the handout of my session].
Personally I enjoyed this week of intense exposure to different aspects of corpus linguistics. Full-week events like conferences and summer schools can be quite draining as you have to be ‘always on’, responding to new contents and people. However, the learning hopefully makes up for that.
There’s been silence from me since November. What has happened in the meantime? Somehow time has been disappearing ever since the academic year started in September, because I started teaching. Not only did I start teaching for the first time, it is also a subject outside my area of expertise. As a result I have been on a steep learning curve both in terms of pedagogy and the subject matter.
Now of course I’m also supposed to be doing my PhD at the same time. I have finished the data collection for my corpus in October. My supervisor has been very keen for me to start writing the actual chapter about the analysis of this corpus. At times I have felt a bit under pressure because I’m afraid that if I’m doing this too quickly I will make mistakes. And I have experienced several times that with corpus linguistics it is very easy to make such ‘mistakes’: not necessarily in terms of really doing something outright wrong but simply ticking (or forgetting to tick) a certain setting option that then makes the results either somewhat wrong, illogical, or at least not ideal. The problem is that often the initial list output from a corpus tool is followed by a considerable amount of manual work (categorisation, interpretation) so that it’s really rather disheartening when you have to redo the list and all subsequent steps.
Apart from all the technical considerations, one of the scariest issues has been this thought: “I have no idea how to write a chapter”. I started my PhD right after the MA, which I had done right after my BA. So I have the experience of 4 years of intense term paper writing. Yet, term papers seem so different. I loved them, actually. Yes, when I had 4 MA term paper deadlines on the same day, the psychological pressure was simply awful (and it happened to me twice – once in each semester). Yet, this shortage of time and the lecturers’ advice to “keep it manageable” was enough to help me refine my thoughts, my structure, my bullet points for each section and the term papers somehow wrote themselves. The PhD is so different. Obviously I wrote a proposal before I even started it (i.e. during the MA!) and I basically spent the first year reading and drafting a tentative literature review and methodology. Now that I am 1.5 years in it seems like I can toss much of that right into the bin… why is that?? But yes of course everyone tells you that. The whole project will shape itself as you proceed and your thoughts will get refined and all that.
Writing BA and MA term papers seems to have been a straightforward process. Either there was a set task and I knew what to do/ look for and therefore what literature to review (at least the literature mentioned in class plus 5-10 articles related to the topic found on Google Scholar or in the library catalogue; often there wasn’t space for a literature review of more than a page anyway). Of course there were moments of desperation. Being somewhat of a perfectionist I did many overnight term paper writing or proofreading sessions, often in the company of classmates in a departmental computer room or a 24-hr library section with lots of chocolate and soft drinks. Nevertheless, there was always this wonderful idea of further examination being “beyond the scope of this paper”. And this scope had been neatly defined in discussion with my lecturer.
For the PhD, then… I am often confused about the scope. Everything shifts and floats and new ideas come up or get rejected. The thought of “writing up” makes me feel really dizzy. Of course I have the lit review and methodology drafts from year one and lots of drafts of what I have been doing in year 2, but I know very well that EVERYTHING WILL HAVE TO BE REWRITTEN. OMG OMG OMG!
Phew… I tried overcoming the little panic attacks that I had when thinking of the transition of term paper to PhD chapter by asking my supervisor very practical questions along the following lines:
Do I need to put lit review bits into the chapter as I’m drafting it now? How do I know which bits need to be moved to the ‘lit review chapter’ (which will have another name) and which stay in the chapter?
[Same for the methodology]: Do I add methodological details into the chapter?
I’m also struggling with the structure of the actual results etc… but anyway, regarding the literature and methodology bits, she basically told me to add the critical bits to the chapter for now and once I rewrite or put together the whole thesis I will find the balance. She actually suggested that it would be neat to have one general methodology chapter that is followed up by a more detailed short methodology section in each analysis chapter relevant to the local discussion there.
I have been writing so many drafts of my current analysis… they all seem to end up like a report rather then a chapter. So she told me to stop trying to find out other things or change the method again but rather add some interpretation and theoretical implications in relation to my research field. This is what I have to do now.
In the meantime I have also referred to one of my favourite procrastination strategies: reading about writing. I have come across two great books for that recently (which you may know already), Writing Your Dissertation in Fifteen Minutes a Day(Joan Bolker) and On Writing(Stephen King). The first one has a title that first sounds a bit ‘cheap’ but I was really positively surprised by the book and it’s so far my favourite PhD guide. In fact, I finished it in four nights. King’s book is of course pitched at writers of fiction. (This was also interesting as I’m involved in teaching a stylistics module). Both books are very easy to read and suggest many interesting writing strategies.
Do you know of any other good books? And what are your strategies for writing a chapter? Sorry for writing such a long post – I needed to let these words out.
I wrote this post 1.5 months ago, in late September 2015. Now that some time has passed and I have played around with WordSmith and Windows on my Mac I think I’m ready to post it.
I have decided to put something relatively practical down today – compared to my previous posts, which were more generally about feelings related to the PhD. I’m about to start the 2nd year of my PhD (until 1 October I like to take advantage of the ‘1st year status’, though) and therefore things must get more practical. There’s still reason to talk about feelings, the nature of academia and a PhD. Yet, at the moment my feelings are actually somewhat dominated by the need to get something practical done. In corpus linguistics practical tasks often have a technical aspect.
In early 2013 at the beginning of my final BA semester I bought a Macbook, because … my relatively cheap Asus laptop had badly crashed twice, requiring a new hard disk (ok, I poured coffee over it…), was generally getting slow and had some pink and turquoise stripes on the display. At that point I was mainly thinking about my final year project which I would have to submit in May. Then I didn’t realise that the area of corpus linguistics, which I had already studied in a BA module, would also become the major focus of my MA and my PhD and that a Macbook might not be the greatest choice for that. [Please feel free to criticise this idea].
The reason that having a Mac is tricky for corpus linguistics is that one of the most popular software packages, WordSmith Tools (WS), does not natively run on a Mac. There are many other options, specifically the freeware AntConc which runs on basically any operating system. [I recently learned about a new tool called corpkit which so far seems a Mac/Linux exclusive though!] Many corpora are also accessible from the web – such as the COCA, the BNC, … If you want to build your own corpus, however, you likely need to have a tool on your own computer (unless you can convince the developers of a system like CQPweb to host it for you). Of course there are more techy options like using programming environments such as R or Python for corpus linguistic analysis. Because of some of the functions available in WS and the fact that my undergraduate and postgraduate corpus linguistics modules were based on this software I still like to use it for some tasks.
Since I had regular access to a campus-based Windows desktop in the first year of the PhD I avoided the issue of installing WS on my mac. Now I might need to do more work from my home office so that the question has popped up. I had heard that you need to install Windows in a virtual environment on your Mac by installing either Parallels or VMware. Each of them costs approximately £70, I believe, add that to the cost of a Windows licence and the effort of installing it all and I wasn’t too excited. Now that I did some research I learned about Oracle’s Virtualbox, and it seems to work as well, but is free. Disclaimer: I don’t know what the potential disadvantages are in installing WS via the free Virtualbox rather than a paid-for virtual environment! (Anyone?) Once I also tried circumventing the step of installing the Windows OS by using the tool WineBottler which allows you to pretend to your Mac that the Windows programme you want to use is actually in a Mac format. This wasn’t successful in my attempt to use WS and there wasn’t support available for this case, probably because corpus tools are not very widely used in comparison to other software (I suppose only linguists, other academics, and some language teacher know about them…).
So here are the steps that I followed for installing WS in a Virtualbox on my Mac:
Download Virtualbox (Oracle, available for free) + its extension pack (this allows you to have shared folders between your Mac and virtual OS, I think – see this video at 22.30 for a guideline of setting up a shared folder)
Install Virtualbox + extension pack
Buy a Windows license (I decided for Windows 7, because that’s the last one I’m familiar with) from a software website & download the operating system (iso file) from there – I found the German site softwarebilliger.de, but I’m sure there are English options available
Install Windows inside a new virtual machine in the Virtualbox. I basically followed the directions in video 1 and video 2. (I settled on 2GB RAM because I have 4GB; 2 CPU because I have 4 and 20GB dynamically allocated space).
The option of setting up shared folders to access the same files from the mac OS and the new Windows OS are explained in video 3 (minute…)
Install the latest version of WS from the Mike Scott’s website – you will need to have a valid license key, which you can purchase from the same site (but if you are a research student it might be worth checking with your university whether they can provide you with one)
The software runs a bit more hesitant than on my previous university PC, but it does show results. How are people’s experiences with Parallels/VMware? For those, do you also need to allocate a certain percentage of your macbook’s RAM. CPU and storage for the virtual machine? How much?
Having used WS on my Mac multiple times now over the course of 1.5 months I’d say it works alright. I can open files and also create keyword lists or concordances without major problems. However, I always have to be careful that I don’t select items or click on buttons too quickly. For example, when I ‘choose texts’ for one of the tools it’s dangerous to hold down the shift key and the downward arrow – usually this makes the whole application freeze and I have to kill it. It’s also worth noting that it’s better not to have too many other programmes running at the same time (also on the Mac OS). This might be a problem of my own computer, though. It’s been bought on a student budget and therefore is one of the slowest Macbook options from 2012.
One issue that came up regarding Windows is that I forgot to activate it at the beginning (although I had a key! – it didn’t force me too, though…). So last week the Windows screen turned black and I got all blamed and shamed by the operating system (this copy is not genuine!). Unfortunately when I tried activating it this didn’t work – the system said I was trying to use a key for the wrong computer. I think this is probably due to confusion caused by the virtual environment. After many stressful attempts at getting through the Microsoft UK customer service hotline I finally got to talk to a human (!) customer service operator who helped me to manually activate my Windows 7…
I am currently attempting to learn something about the programming language R. Why? Is that even a good idea?
At a few points during the past few years I have considered whether I chose the wrong degree(s). My BA degree was called “English Studies for the Professions (BAESP)” and I really enjoyed it and found everything interesting. At the same time I wanted to get more involved with research and see how linguistics can get really useful. So I moved on to an MA in Applied Linguistics and finally a PhD in the same field. I am really interested in linguistics and think it is a worthwhile area. BUT at times I wonder “Why didn’t I study computational linguistics?” Since my research deals with corpus linguistics this is actually not so far of a stretch. The problem is that I don’t seem have a computational mindset… So far the only type of computational stuff that I can more or less deal with is interactive. During the MA we did some work with the statistical package SPSS which used to be command-driven but now has an interactive interface. For corpus linguistic analyses I have used WordSmith Tools, AntConc and SketchEngine, which are all more or less user-friendly. If anything I get confused by too many buttons and settings that are offered.
When and how did I decide to do something about my non-computational situation?
I have been playing with the thought of getting a little bit more tech-savvy (and at the same time brush up on my understanding of statistics) for a year or so. Throughout my studies I have simply come across so many studies where people do more interesting stuff than I seem to be able to do because I don’t know how to make something like that happen. An example is a Twitter study that I already quoted in my BA project (which was also about Twitter). For my own project I used an online tool (at the time it was called TAGS v3 now there is TAGS v6) to collect a limited number of Tweets, leading to a small corpus. Michelle Zappavigna (@SMLinguist), in her book Discourse of Twitter and Social Media, however, had access to the infrastructure and support necessary for downloading and compiling a large Twitter corpus containing over 100 million Tweets. She used a Python script and the Twitter API. At that time I thought that I’m never going to be able to either do this myself or have the required technical support. While I still don’t know how to do this my attitude has changed slightly. I’m lucky to be cooperating with people from statistics and programming for a project coordinated by my supervisor. This regular interdisciplinary contact has taught me there are things that seem infinitely difficult to me but can easily be done by others in a short amount of time with a few lines of code. Moreover, the cooperation is gradually showing what kind of things are actually possible with programming. In the meantime I have been wondering whether or not it is worth investing time and energy (and money I guess) for learning some baby steps in programming when there are so many experts out there? Well, I don’t know, but I am trying to regain some control over my work…
Here are some interesting view points on coders and coding expressed by Paul Ford in that recent Bloomberg code issue:
Coders are people who are willing to work backward to that key press. It takes a certain temperament to page through standards documents, manuals, and documentation and read things like “data fields are transmitted least significant bit first” in the interest of understanding why, when you expected “ü,” you keep getting “?”
Regarding the question whether or not to learn coding, Ford says:
There’s likely to be work. But it’s a global industry, and there are thousands of people in India with great degrees. […] I’m happy to have lived through the greatest capital expansion in history, an era in which the entirety of our species began to speak, awkwardly, in digital abstractions, as venture capitalists waddle around like mama birds, dropping blog posts and seed rounds into the mouths of waiting baby bird developers, all of them certain they will grow up to be billionaires. It’s a comedy of ego, made possible by logic gates. I am not smart enough to be rich, but I’m always entertained. I hope you will be, too. Hello, world!
[print pp. 109-112, digital Section 7.5]
Personally, I don’t think I can now start to become ‘a real coder’ and ‘compete’ with all those computer science graduates and other professional coders. BUT, the whole thing seems fascinating and if I know a little bit some light might be shed on so many areas that are still dark for me.
I saw info about the ‘Regression modelling for corpus linguistics‘ workshop by the linguist Stefan Gries (held in Lancaster, 20 July) and knew about his books (Quantitative Corpus Linguistics with R – QCLWR – and Statistics for Linguistics with R) so I finally decided to buy them. That’s really the main point for me. [By the way, in the book, Gries argues that R is particularly well-suited for corpus linguistics…] While I know other resources are available, such as MOOCs (I even attempted a MOOC on R but dropped out), I need to see something that’s relevant to my own research (the R MOOC I attempted used data from biology, I believe). Having said that the MOOC introduced a neat little learning environment called ‘Swirl‘ which allows you to “learn R, in R”. I might go back to that at some point. Actually, it’s even hard for me to get through the first 100 pages of Gries’ QCLWR because it’s about the basics with few linguistic applications. But I try to motivate myself to continue by flipping beyond the 100 pages now and then because I can see that soon I’ll be soon (hopefully) able to apply those basics to linguistic problems (I’m almost at page 96 now – yay!). So if someone had made a book about Python for corpus linguistics (is there one?), I might have gone for that, because I didn’t really know anything about which language is best to know. However, I am looking forward to a session at the Nottingham Summer School in Corpus Linguistics entitled ‘Essential python for corpus linguists’ run by Johan de Joode.
My main problems so far
Unfortunately, I am still lacking the coding mindset, but I hope that will change after working through the second, more applied linguistics part of QCLWR. I haven’t done proper math since high school and this step-wise logical thinking about embedding logical/ regular expressions and loops and variables and whatnot all feels a bit foreign to me. More often than not I can’t follow the examples at first sight (usually because I have missed a parenthesis somewhere…). Just have a look at an example of the lines that I have been trying to work through… (Gries, 2009: 89):
I also have difficulties with remembering function names and their argument structures and, worse still, I can’t really follow the R/ RStudio help entries about the functions. The biggest problem is that it takes me ages to go through the tutorial in Gries’ QCLWR. There are still more than a hundred pages left including masses of exercises and assignments and the second book (Statistics for linguists with R) is still waiting for me… Obviously this is not even the only task I’m supposed to be doing for my PhD at the moment…
On the bright side, though, I am slowly starting to feel more comfortable staring at condensed strings of digits and characters and slowly picking up the ability to analyse a command string step by step. Once something does work it really delights me.
What are your experiences with starting to code? Do you think it’s worthwhile to invest in these skills? Which programming language are you learning and why? [And sorry for turning this into such a long post…]
Meaning: “To defiantly display one’s opinions and beliefs. Also, to show one’s intention to hold on to those beliefs until the end” (phrases.org.co.uk).
This blog post is inspired by my recent first year confirmation review. The review was actually a positive, encouraging and also refreshing experience. I received numerous pieces of valuable advice. One point, though, stuck with me most and this was the motto “nail your colours to the mast”. This seemed to be the examiner’s main concern (and I shamelessly quote his saying about the colours here). What’s the actual theoretical approach that the project is based on?
As the author of the report, having spent like half a year on it, I can testify that this has really been the main struggle. In writing my literature review I had spent plenty of time on locating different positions in the literature and identifying potential differences between the different approaches. This was at times a frustrating endeavour, as ever so similar terms were used for frameworks with only very subtle differences. Coping with this diverse, overlapping terminology has been a key issue. Mapping out the different terms and their usage had already cost quite a bit of energy. I understand that I fell short on the next step – evaluating them and picking one for my work or even making up another term (and of course justifying it!).
Whose side am I on? To me as a first year PhD student it is just a scary thought to have to make such a decision. If I take up a specific term (such as, in my case, ‘corpus-assisted discourse analysis’ rather than ‘corpus-based/driven’), do I need to then follow the scholars associated with this terms for the rest of my work? Will I contradict myself if I choose one term and at a later stage take a turn with my work that doesn’t really harmonise with the work of the related people? How do I know the implications? Due to some of these daunting questions, I attempted to stay on ‘friendly terms’ with various approaches. This, however, is problematic in itself.
Is it possible to decide on a different set of colours at a later point? (The definition for the colour metaphor quoted above seems to suggest this, but maybe in academia we can allow for more flexibility? Clearly we’re all evolving and learning?) The saying was new to me, but in the context of the confirmation review I understood what was meant – clearly express what you’re trying to achieve and how you are doing that. I think I did that fairly well in my methods section (although at times it needs simplification as I was told) – in the parts that are very practically oriented. I have noticed that I struggle more with attempting to explain the theoretical implications of my work. And I believe this problem is routed in the fear that I misuse theoretical claims, for instance by combining incompatible approaches.
At the end of the review meeting both my examiner and supervisor emphasised, however, that it is okay (and probably even good!) to keep an open mind throughout the PhD and refine your theoretical standpoint through continuous writing. That made me feel more relieved. Still, I have had to go back to more reading on the terms I wasn’t sure about (this includes the definition of ‘discourse’ – a real can of worms…).
What are your views on this topic? Have you encountered similar difficulties?
As you may have gathered from somewhere on this page my name is Viola. I am still a first year PhD student (although the end of year is approaching…) and a slightly longer paragraph about myself can be found on my profile. Here is a recent photo of me at ICAME 36 two weeks ago, where I had the chance to thank the organisers for the wonderful conference. (Many thanks to Sebastian Hoffmann for this shot – more of his photos from the conference are shown in this gallery).
Ever since I started my PhD in October 2014 the idea of starting a blog has been popping up at various trainings and it’s something I’ve observed others do very well. I like the notion of documenting the ‘PhD journey’. During my PhD life I have already started becoming a lot more active on Twitter – follow me at @violawiegand. I am excited that many people in ‘my’ academic field (here I mainly mean corpus linguistics – see the corpus linguistics Twitter list I compiled) are sort of permanently on Twitter, often giving me new ideas and just showing me what developments are out there. At the same time I also enjoy viewing encouraging posts on writing advice and other aspects of grad/PhD/academic life as documented in my ‘writing’ Twitter list. I hope to somehow join these two crowds with this blog.
So what’s the blog going to be about?
I’m still considering that but it will probably document what I’m concerned with as my PhD continues. My topics of interest include:
increasingly also more computational topics – now learning to work with R 🙂
I also welcome feedback from more experienced bloggers regarding what’s best to focus on in a PhD blog and what’s perhaps rather boring for all of you to read. Anyhow, I’m excited about this step and hope that the blog will interest some of you and provide myself with a fresh view on my work.