TY - JOUR

T1 - Кто Виноват? Паттерны присвоения вины и ответственности в сетевых дискуссиях об иммигрантах в россии и германии

AU - Bodrunova, Svetlana S.

AU - Smoliarova, Anna S.

AU - Achkasova, Vera A.

AU - Blekanov, Ivan S.

PY - 2018

Y1 - 2018

N2 - The conflicts between host communities and re-settlers from global or post-Soviet 'South' and public discussions on such conflicts have become a vivid feature of today’s public spheres in both Europe and Russia. Discussions in social media may put pressure upon immigration policing, as they reflect both consensual and conflictual public moods. Thus, it is crucial to know who (including actors and institutions) social media users see as the culprits in this conflict and who is expected to resolve these problems. We look at four Twitter discussions on the conflicts involving re-settlers in Russia and Germany of 2013–16 and assess whether the user type correlates with blaming and responsibility patterns. We also describe the discursive strategies of blaming in the two countries. The methods of data collection and analysis include vocabulary-based web crawling, expert evaluation of user types, manual coding of tweets, and descriptive statistics. Our results suggest that, contrary to expectations, the blaming patterns are similar: the main blame is put on regional authorities and police, federal government and national leaders, and immigrant groups. While blaming them, people expect the resolution of the conflicts from the federal government, who is seen to be responsible for immigration policies. Also, while in Germany we detect fierce mutual blaming by pro-nationalist and feminist groups partly compensated by neutral media discourse, in the world of Russian Twitter, we see a one-sided blaming of authorities and immigrants in the absence of institutional mediation of the discussion, as well as low expectations of non-violent political resolutions of inter-ethnic tensions.

AB - The conflicts between host communities and re-settlers from global or post-Soviet 'South' and public discussions on such conflicts have become a vivid feature of today’s public spheres in both Europe and Russia. Discussions in social media may put pressure upon immigration policing, as they reflect both consensual and conflictual public moods. Thus, it is crucial to know who (including actors and institutions) social media users see as the culprits in this conflict and who is expected to resolve these problems. We look at four Twitter discussions on the conflicts involving re-settlers in Russia and Germany of 2013–16 and assess whether the user type correlates with blaming and responsibility patterns. We also describe the discursive strategies of blaming in the two countries. The methods of data collection and analysis include vocabulary-based web crawling, expert evaluation of user types, manual coding of tweets, and descriptive statistics. Our results suggest that, contrary to expectations, the blaming patterns are similar: the main blame is put on regional authorities and police, federal government and national leaders, and immigrant groups. While blaming them, people expect the resolution of the conflicts from the federal government, who is seen to be responsible for immigration policies. Also, while in Germany we detect fierce mutual blaming by pro-nationalist and feminist groups partly compensated by neutral media discourse, in the world of Russian Twitter, we see a one-sided blaming of authorities and immigrants in the absence of institutional mediation of the discussion, as well as low expectations of non-violent political resolutions of inter-ethnic tensions.

KW - Germany

KW - Immigrants

KW - Inter-ethnic conflict

KW - Russia

KW - Twitter

UR - http://www.scopus.com/inward/record.url?scp=85061576777&partnerID=8YFLogxK

U2 - 10.17323/727-0634-2018-16-4-627-644

DO - 10.17323/727-0634-2018-16-4-627-644

M3 - статья

AN - SCOPUS:85061576777

VL - 16

SP - 627

EP - 644

JO - ЖУРНАЛ ИССЛЕДОВАНИЙ СОЦИАЛЬНОЙ ПОЛИТИКИ

JF - ЖУРНАЛ ИССЛЕДОВАНИЙ СОЦИАЛЬНОЙ ПОЛИТИКИ

SN - 1727-0634

IS - 4

ER -