Quantitative Analysis of Bloggers Collective Behavior Powered by Emotions

Large-scale data resulting from users online interactions provide the ultimate source of information to study emergent social phenomena on the Web. From individual actions of users to observable collective behaviors, different mechanisms involving emotions expressed in the posted text play a role. Here we combine approaches of statistical physics with machine-learning methods of text analysis to study emergence of the emotional behavior among Web users. Mapping the high-resolution data from digg.com onto bipartite network of users and their comments onto posted stories, we identify user communities centered around certain popular posts and determine emotional contents of the related comments by the emotion-classifier developed for this type of texts. Applied over different time periods, this framework reveals strong correlations between the excess of negative emotions and the evolution of communities. We observe avalanches of emotional comments exhibiting significant self-organized critical behavior and temporal correlations. To explore robustness of these critical states, we design a network automaton model on realistic network connections and several control parameters, which can be inferred from the dataset. Dissemination of emotions by a small fraction of very active users appears to critically tune the collective states

Micro, Meso, and Macro Data Collection and Analysis, as a Method for Speculative and Artistic Exploration

In this work, an attempt is made to explore the emerging computationally-enhanced private and public environments by analyzing their ecological transitions and its implications on practical, aesthetic, and speculative dimensions. The author has decided to methodologically dissect the multiplicity of information that exists on many possible-to-detect scales (micro, meso, macro), and utilize this extraction as a tool for experimentation and redefinition. With the use of custom-made hardware and software utilities (sensor devices, sentiment analysis algorithms, online APIs, and many more), a vast amount of data is collected and used as a multidimensional layered architecture that constantly shifts and transforms. The extracted and analyzed content of the collection becomes the essence of the work that is shaped and refined through digital and physical making – middleware, recursion, mapping – and by utilizing technological objects within the physical space, the creative process is augmented and amplified, exploring not only new practices and novel applications, but rather redefining behavior, thought-process, and context