Week 4: Building a dataset

In this workshop, we focused upon building a dataset, beginning with a brief reminder of key concepts including cases, values, variables and operationalisation. This was a great time to refresh information learned in my undergraduate degree. Following this, I found my own variables I could collect, being as specific as possible by identifying the specific type of variable, the value it takes (which involved operationalisation) and considering how these data could be useful for research. I opted to look at the subculture of 'Football Twitter''s reponses to the below Tweet on X (fka Twitter) on a serious matter about gambling and addiction:

My outcomes were as follows:

Something to reflect upon with operationalisation is that some values could be ambiguous, or subjective - for example, whether a post on X (fka Twitter) is 'serious' or 'satirical / unserious'. There could be a risk of different people entering data following the same protocol.

I then built a full 150-strong dataset on Excel. I opted to use four of the five variables as above, with the fifth now focusing on the account's anonymity. I felt that with these various variables and data in question, there could be hypothetical routes to explore in terms of 'Football Twitter' subculture, its attitude and user habits, any patterns of behaviour and how it deals with serious matters at hand such as this. I could draw upon literature concerning online, sport and meme culture.

Week 5 then entailed data visualisation, check that out here.