Reductions in Social Network Visualizations
ARTICLE: 'Reductions in Social Network Visualizations' (by @ellenbijster) #bigdata #dataviz #truthclaim
Apart from the well known privacy concerns, there seems to be a general enthusiasm in social studies and the humanities about the availability of large data sets for research through the APIs (Application Programming Interfaces) of sites like Facebook and Twitter. Big Data is surrounded with an aura of objectivity, accuracy and truth. This is why having the computing power to process, scrape, clean and visualize these social data sets can feel like we are closing in on the holy grail of social science: the bigger the data, the bigger the insights? This paper aims to critically investigate what insights can actually be gained from social network visualizations by analyzing the technical process of visualizing Big Data, the underlying assumptions of visual representations of networks, and the contextual limitations of social network data.