This workshop session had us split into groups to each consider one of the six ‘V’s of big data: variety, value, volume, velocity, veracity and variability. The three hours were split in two, each part session opened by a number of speakers presenting the findings of the papers they had contributed to the forthcoming Sage Handbook of of Social media Research Methods. We were asked to consider our ‘V’ (we had Variety) in the context of any tension between Big and small data, if indeed there was any. Our table, as it transpired, consisted of social scientists rather than computational scientists, so unsurprisingly tended to focus on the positive aspects of small data.
I found the opening presentation by Claudine Bonneau and Mélanie Millette on their ‘small’ data projects spoke to my research – very much a hands-on, immersive, participatory approach, where tweets were collected and analysed manually. The approach within the long-term observation was described as ‘agile’, following the conversations from place to place. There’s a resonance for me in the way teachers shift between Twitter, #chats on Twitter and blogs when discussing their practice. I yet to grasp how or if I can or should incorporate the offline places where these discussions occur. There are clear sites of interest where teachers gather to discuss and share practice (TeachMeets etc); my problem however, will be whether I have the scope to chase them down.
I found the topic of ‘Working out Loud’ practice on Twitter had a close fit with my own research, although I was surprised that other professions also engaged in this practice (how insular am I?!). However, the most compelling aspect was how we ‘thicken’ small data, perhaps reducing its breadth whilst enhancing its depth.