TIA125 - Data Cleaning Workshop.pptx

The slides from the workshop are above: they contain hidden slides with tutorials for solving common issues in data

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Date / Time: Tuesday 6th December, 10:00-12:00
Place: Torg 3 (331)
Facilitator: Tanya Osborne
Contact: tanya.osborne@gu.se

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Welcome to a workshop on Data Cleaning!

To take part in this session, you should:

Be prepared to work in your project group
Bring along a laptop, or coordinate someone in your project group having a laptop
Bring any questions about your dataset

The plan for this workshop is that I will first talk you through some of the basic process for cleaning data, and then we will have some groupwork where you can work through and identify problems in your own data. We'll then discuss this together as a group, and I'll do some practical tips based on the problems that you see in your own data. By the end of the session you should understand how to get your data into an analysable state.

This kind of work can be done in many different programs and software. I will mostly be using Excel to demonstrate techniques to you, but you can equally use SPSS, R, SQL, Python, Google Sheets, and many more. The concepts are all transferrable to whatever software you have.

Excited to meet with you all and hear more about the projects you have chosen!

Optional Readings

The SAGE Handbook of Social Media Research Methods has a chapter on processing social media data. You might find the section in this chapter about data cleaning helpful in understanding the common types of errors that are present in social media data: https://sk-sagepub-com.ezproxy.ub.gu.se/reference/the-sage-handbook-of-social-media-research-methods/i1376.xml

McKenna et all (2017) in their paper Social media in Qualitative Research: Challenges and Recommendations, discuss in detail their process for collecting threads from Blizzard's World of Warcraft forums. You might find section 4 of this paper interesting if you're curious about text mining (which we won't talk about so much in the workshop) or want an example of writing about processes when analysing social media data: https://www.sciencedirect.com/science/article/pii/S1471772717300957