The kommuna impulse: collective mechanisms and commune-ists in the early Soviet State

This study examines the creation of the urban kommuna (commune) and the ideals that stimulated this social phenomenon – the kommuna impulse of the nascent Soviet state. Collective idealism affected Soviet housing, architecture and even urban planning, but little is known of social experiments in commune‐ism. As a result, these collective cells have been dismissed as utopian anomalies or the product of a housing shortage. Here it is argued that these discursive assessments are unsatisfactory and isolated from the historical narrative. While utopian ideals and domestic necessity were central to the formation of collective living, the kommuna was also involved in an active discourse with collectivism and socialist ideology. The kommuna cell was a dynamic entity that required considerable formative planning. The activists who forged these cells – the self‐identified ‘communards’ – turned their everyday domestic life into a socialist battleground, in which they struggled with the key debates of the early Soviet state. This article examines the communard as a social activist in order to better understand this phenomenon. It clarifies the coexistence of ideological and idealist trends among Soviet youth with practical contingencies for socialism. Furthermore, it reveals the process by which the kommuna impulse and these contingencies developed throughout the 1920s and early 1930s.

In the mood: the dynamics of collective sentiments on Twitter

We study the relationship between the sentiment levels of Twitter users and the evolving network structure that the users created by @-mentioning each other. We use a large dataset of tweets to which we apply three sentiment scoring algorithms, including the open source SentiStrength program. Specifically we make three contributions. Firstly we find that people who have potentially the largest communication reach (according to a dynamic centrality measure) use sentiment differently than the average user: for example they use positive sentiment more often and negative sentiment less often. Secondly we find that when we follow structurally stable Twitter communities over a period of months, their sentiment levels are also stable, and sudden changes in community sentiment from one day to the next can in most cases be traced to external events affecting the community. Thirdly, based on our findings, we create and calibrate a simple agent-based model that is capable of reproducing measures of emotive response comparable to those obtained from our empirical dataset.