Warwick Q-Step Masterclass: Quantitative Text Analysis

Warwick Q-Step Centre and the Faculty of Social Sciences

The Warwick Q-Step Centre Masterclass on Quantitative Text Analysis

Radcliffe Conference and Training Centre

<p><strong>PLEASE DO NOT REGISTER FOR THIS EVENT IF YOU HAVE NO INTENTION OF ATTENDING.</strong></p><p>Although places are free to students, the Q-Step Centre incurs substantial costs for these events which cannot be refunded in the event that registered students do not turn up on the day. Please make every effort to inform us in advance of the event if you are unable to attend or you can cancel your place directly on Eventbrite.</p><p>The Warwick Q-Step Centre is delighted to host this Masterclass on Quantitative Text Analysis, delivered by Dr <a href="https://research.vu.nl/en/persons/kasper-welbers" target="_blank" data-msys-clicktrack="0" rel="nofollow noopener noreferrer">Kasper Welbers</a> - Assistant Professor at VU University Amsterdam.</p><p>This Masterclass is aimed primarily at postgraduate students on our 3 Quantitative Social Science degrees. Final year Q-Step undergraduate students, interested in learning enhancement opportunities, are also invited to attend. Depending on numbers we may be able to open the event up to PG students in other relevant subject areas throughout the University.</p><h2>Quantitative Text Analysis</h2><p>Quantitative text analysis is the process in which quantitative information is systematically extracted from textual content. Initially, this process required trained human coders that had to manually read the texts, but today there are also many effective computational techniques that enable new and more efficient ways to extract this information. In an age of digital communication, where unprecedented volumes of textual data from various aspects of life are publicly available, this has become an exciting new method in the social sciences and humanities.</p><p>In this master class, you will learn the fundamental concepts of computational text analysis, and get hands-on experience in working with state-of-the-art techniques in the R statistical software. We will start with a session on importing, cleaning and preprocessing texts. Second, we will discuss three main branches of analysis techniques---rule-based, supervised and unsupervised---and you can practices with the technique(s) of your choosing. Third, we will dedicate attention to validation, which is a critical step that is all to often brushed over. Finally, we will reserve some time where you can consult me regarding your own (future) project, or practice with (additional) tutorials.</p><h2>Computing Requirements</h2><p>Each session will start with a lecture introducing the fundamental concepts and demonstrating techniques in R, and then move to a hands-on workshop where you will apply techniques yourself. Please make sure to bring your own laptop (and power cable) with the latest release of R and Rstudio. Also, please try to install the “quanteda” and “corpustools” packages beforehand (this should be painless in most cases, but they have some tricky dependencies). </p><h2>Literature </h2><p>Material will be provided in the workshop. For further reading:</p><p>The structure of the workshop will be loosely based on this article:</p><p>•	Welbers, K., Van Atteveldt, W., &amp; Benoit, K. (2017). <a href="https://www.researchgate.net/publication/320820767_Text_Analysis_in_R" target="_blank" data-msys-clicktrack="0" rel="nofollow noopener noreferrer">Text analysis in R. Communication Methods and Measures, 11(4), 245-265</a>.</p><p>For more in-depth information and discussion on computational text analysis in research:</p><p>•	Grimmer, J., &amp; Stewart, B. M. (2013). <a href="https://www.cambridge.org/core/journals/political-analysis/article/text-as-data-the-promise-and-pitfalls-of-automatic-content-analysis-methods-for-political-texts/F7AAC8B2909441603FEB25C156448F20" target="_blank" data-msys-clicktrack="0" rel="nofollow noopener noreferrer">Text as data: The promise and pitfalls of automatic content analysis methods for political texts. Political analysis, 21(3), 267-297</a>.</p><p>•	Wilkerson, J., &amp; Casas, A. (2017). <a href="https://www.annualreviews.org/doi/abs/10.1146/annurev-polisci-052615-025542https://www.annualreviews.org/doi/abs/10.1146/annurev-polisci-052615-025542" target="_blank" data-msys-clicktrack="0" rel="nofollow noopener noreferrer">https://www.annualreviews.org/doi/abs/10.1146/annurev-polisci-052615-025542https://www.annualreviews.org/doi/abs/10.1146/annurev-polisci-052615-025542</a></p><p>A basic understanding of linguistics and natural language processing is strongly encouraged. This is a classic:</p><p>•	Jurafsky, D. &amp; Martin, J.H (2008). Speech and language processing (2nd edition). </p><p>o	<a href="https://web.stanford.edu/~jurafsky/slp3/" target="_blank" data-msys-clicktrack="0" rel="nofollow noopener noreferrer">Third edition hopefully soon</a> (links contains draft chapters)</p><p>For the R side of things, there are many free resources available online. A short list:</p><p>•	Colleagues and I maintain a <a href="https://github.com/ccs-amsterdam/r-course-material" target="_blank" data-msys-clicktrack="0" rel="nofollow noopener noreferrer">GitHub page with R course material</a>, including text analysis tutorials </p><p>•	the quanteda packages has a great <a href="https://tutorials.quanteda.io/introduction/" target="_blank" data-msys-clicktrack="0" rel="nofollow noopener noreferrer">tutorial website</a></p><p>•	R package vignettes for text analysis packages, such as <a href="https://cran.r-project.org/web/packages/stm/vignettes/stmVignette.pdf" target="_blank" data-msys-clicktrack="0" rel="nofollow noopener noreferrer">stm</a>, <a href="https://cran.r-project.org/web/packages/spacyr/vignettes/using_spacyr.html" target="_blank" data-msys-clicktrack="0" rel="nofollow noopener noreferrer">spacyr</a>, <a href="https://cran.r-project.org/web/packages/corpustools/vignettes/corpustools.html" target="_blank" data-msys-clicktrack="0" rel="nofollow noopener noreferrer">corpustools</a>, <a href="https://cran.r-project.org/web/packages/udpipe/vignettes/udpipe-annotation.html" target="_blank" data-msys-clicktrack="0" rel="nofollow noopener noreferrer">udpipe</a></p><h2>PLEASE NOTE: </h2><h3>This event is for Warwick University students only. There is no option to attend parts of the Masterclass, you must be able to attend for the whole day.</h3><p>Attendance is free and refreshments, including lunch, will be provided. Registration is required as places are strictly limited. So book your place now!</p><p>Further information about the Warwick Q-Step Masterclass Programme 2019/20 can be found on our <a href="https://warwick.ac.uk/fac/cross_fac/q-step/study/masterclasses/schedule1920" target="_blank" data-msys-clicktrack="0" rel="nofollow noopener noreferrer">website</a>.</p>

Warwick Q-Step Masterclass: Quantitative Text Analysis

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