Through our Digital Methods program, we offer a regular series of research training workshops to our own PhD students, and we are able to develop bespoke training modules for a range of organisations. Below is a sample of the workshops that we currently offer, but contact us via email@example.com to discuss your training needs.
Advanced Social Media Analytics
Particularly when working with large social media datasets, quantitative and mixed-methods approaches that draw especially on visual representations of ‘big data’ are now an indispensable part of the scholarly research and publication process. This data analytics and visualisation module focuses on a number of emerging standard tools and methods for large-scale data analytics, using Twitter data to illustrate these approaches. The module introduces participants to the open-source Twitter Capture and Analysis Toolkit (TCAT) as a capable and reliable tool for data gathering from the Twitter API, and to the high-end data analytics software Tableau as a powerful means of processing and visualising large datasets. The skills gained in the module are also transferrable to working with other large datasets from social media and other sources.
Social Media Issue Mapping
Issue Mapping is an advanced method for making sense of the social media conversation around topics where there is a lot of uncertainty or disagreement—from science and the environment to popular culture and gender. In this module, you will use a variety of tools for tracking hashtags and media objects across platforms in order to build an inventory and map of key media objects (including hashtags, URLs and audiovisual texts) and to map the issue networks associated with digital media controversies.
Instagrammatics – analysing visual social media
This module’s exploration of visual social media uses Instagram as a focus but with applications beyond this specific platform. The module provides a hands-on means for approaching visual social media, giving participants the opportunity to interrogate what they might do with such data and what visual media and methods might contribute to research.
In digital media research it is often necessary to collect large amounts of data (text, images) from one or a set of web sites that do not offer a structured Web API. During this module you will learn how to build simple tools that allow you to efficiently collect and store such data for subsequent analysis. We will use two different approaches to build these tools based on off-the-shelf online services and we will look at how it is possible to build a bespoke webscraper for your project using a programming language called “Python”. This module does not require any previous knowledge of computer programming, but you will find it easier to follow the exercises if you have some knowledge of basic web technology, such as HTML.
Software and app studies
In order to study the social media platforms and software applications that populate the digital media environment, we need to take into account not only content and user practices, but also socio-technical features, interface design elements, and business models ¬but doing this empirically is a challenge. In this module, you will be introduced to a novel approach to critical and qualitative digital methods: the App Walkthrough, which borrows from vernacular digital media culture, User Experience research and STS to undertake an “ethnography of affordances”, as part of a broader software and app studies approach to mobile dating and hook-up applications.
Using agent-based simulation methods to analyse complex dynamic systems
Many phenomena in our field are inherently complex and dynamic: They change over time; everything is connected to everything else; they have “tipping points” or “virtuous” (or “vicious”) circles; and so on. Our traditional methods are often lacking in the analysis of such systems. This module you will be introduced to agent-based modelling (ABM), which is a method that has proven to be a useful alternative for unpacking complex and dynamic phenomena. During the module you learn how to build a model and run simulations with NetLogo. Prerequisites: Basic coding experience is not a requirement, but might be useful.
Analysing and visualising geospatial data
Spatial information, or geodata, is a rapidly growing subset of big data. Social media platforms that rely on location-based services, as many do, are increasingly geosocial, generating large, real-time geodata sets. This workshop will focus on the particular challenges facing socio-cultural researchers in relation to accessing, analysing, and visualising spatial information, particularly in regard to geosocial media data. The workshop will provide a practical introduction to using the web-based mapping platform Carto to visualise and spatially analyse geodata. The ethics and limitations of dealing with geosocial data will also be explored.
Build a bot: Browser automation with Selenium and Python
In this module you learn how to build a computer program that controls a web browser and mimics the behaviour of a human online user. This is a very useful technique that can be used in a range of studies, such as the examination of how gender bias is implemented by an online platform’s algorithms, or perhaps just as a straight-forward way to automate access to a search engine. You will build the bot in Python and use a browser automation package called Selenium. In addition to building a bot that can do some basic work for us, we will also discuss legal and ethical issues related to this technique and what it adds to other techniques for online data collection (such as API access and HTTP programming).