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 the analytics process. This data analytics and visualisation workshop focuses on a number of emerging standard tools and methods for large-scale data analytics, using Twitter data to illustrate these approaches. It 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 workshop are also transferrable to working with other large datasets from social media and other sources.
For ODI Open Data Skill Level
You will learn:
- tools and methods for large-scale data analytics
- how to use the open-source Twitter Capture and Analysis Toolkit
- how to use Tableau when working with large datasets
- transferrable skills when working with large datasets generally
Who is this course suitable for?
Advanced Social Media Analytics is ideal for those at the 'Explorer' level of the ODI's Open Data Skills Framework. It's designed to give you a comprehensive introduction to large-scale data analytics, answer questions you might have and leave you thinking about what you might do next.
It is suitable for government employees, private organisations, researchers, academics and students. Participants of previous courses have included: decision makers, managers, public servants, researchers, policy advisors, journalists, non-profit organisations, students, strategists, data owners and publishers.
What prior knowledge do you need?
No previous experience of data is required.
What to bring
A Wi-Fi enabled laptop, on which you have access to install software. To save time, pre-install
What we provide
Morning Tea (tell us if you have any special dietary requirements)
3 hours (9.30am to 12.30pm). Arrive between 9.00 and 9.30am.
Dr Axel Bruns is a Professor in the Digital Media Research Centre at Queensland University of Technology in Brisbane, Australia, and was a Chief Investigator in the ARC Centre of Excellence for Creative Industries and Innovation (CCi). He is the Vice-President of the Association of Internet Researchers. Bruns is the author of Blogs, Wikipedia, Second Life and Beyond: From Production to Produsage (2008) and Gatewatching: Collaborative Online News Production (2005), and a co-editor of Twitter and Society (2014), A Companion to New Media Dynamics (2012) and Uses of Blogs (2006). Bruns is an expert on the impact of user-led content creation, or produsage, and his current work focusses on the study of user participation in social media spaces such as Twitter, especially in the context of acute events. His research blog is at http://snurb.info/, and he tweets at @snurb_dot_info. See http://mappingonlinepublics.net/ for more details on his current social media research.
Tuesday 18 July 2017 from 9.00am for a 9.30am start to 12.30pm at our training facility at TC Beirne Building, 315 Brunswick St, Fortitude Valley, Brisbane.
Cost: $250 + GST
About the Digital Media Reserarch Centre (DMRC)
QUT's Digital Media Research Centre (DMRC) conducts world-leading research that helps society understand and adapt to the social, cultural and economic transformations associated with digital media technologies. The DMRC aims to:
- conduct transformative research in digital media, communication and cultural studies, generating significant new findings and world-leading methodological innovation
- collaborate across QUT, and with a range of government, community, and industry partners to undertake applied research that helps to solve significant, complex problems for our culture, society and economy
- provide a vibrant, supportive and innovative research training environment for our research students, partners and clients.
ODI Queensland is pleased to offer Advanced Social Media Analytics in partnership with the DMRC.