On 1st January 2014 restrictions were lifted on the migration of Romanians and Bulgarians to the UK. Leading up to this date and since then, heated debate has ensued about the impact of this migration. Discourses and images of the country being swamped by this new ‘other’ have proliferated.
Our aim is to investigate how these debates were discursively constructed over the micro-blogging platform Twitter over a five month period October 1, 2013 and March 1, 2014. We draw on understandings of how the nation and national identity is reproduced in established nation-states of the ‘West. Billig (1995) sought to draw our attention to the familiar, habitual, unconscious ways in which the nation is flagged in countries like Britain, which he terms ‘banal nationalism’. But in recent years Billig has been criticized for maintaining a separation between ‘banal’ and ‘hot’ nationalism. Skey (2009) and Jones and Merriman (2009) argue that we cannot assume that nationalism is banal for everyone who lives in Britain at the current time, given the complexity of group identities. Skey, and Jones and Merriman advocate for a notion of everyday nationalism, which incorporates banal and mundane processes but may also include a variety of hotter “differences and conflicts” that affect people’s lives on a habitual basis. The notion of everyday nationalism brings into focus the ways in which people make sense of and/or resist nationalisms emanating from the state. For our research, the notion of everyday nationalism suggests two research questions:
- How do individuals, rather than politicians or the media, shape ideas of who can belong to the nation?
- Do micro-blogging platforms enable heightened nationalism and anti-immigrant discourses or do they also provide a platform for challenging such discourses?
We purchased all status updates on the social media platform Twitter created between October 1, 2013 and March 1, 2014 containing the words "immigration," "immigrant," "migration", or "migrant," and Bulgaria/Bulgarian, Romania/Romanian, England, UK, or Britain. This five-month period allowed us to examine how the conversation around immigration was shaped by the defining event of the lifting of restrictions on Romanian and Bulgarian migration on 1st January 2014.The sample contains 136,960 tweets.
The first stage of analysis involved quantitative network analysis to explore differences among users with a high degree of network centrality for the months of October and December. Specifically, we analysed all tweets that were in the 90th percentile of influence, which we define here as the 90th percentile of the total number of retweets received per tweet. For a tweet to be in the 90th percentile it needed to receive at least 3 retweets in October and 3.4 retweets in December.
The second stage of this research involved qualitative discourse analysis of a five percent random sample of tweets for the month of October and December. This stage was focused on investigating the migration/immigration discourses embedded in tweets from ‘lone users’ or users that exhibited a low degree of network centrality, and whether, and how, these discourses shifted over time.
As expected, quantitative analysis reveals that the most influential accounts in each month are typically mainstream media outlets and other leading social media sites. Additionally, the connectedness of these most influential accounts appears to increase over time. Distinct from much research based around "hashtags," however, our focus on related but different key terms produces a sample with a relatively large portion of isolates and very small conversations. Thus, one descriptive finding is that during this period of heightened immigration salience, the ‘conversation’ on Twitter was generally decentralised and not overwhelmingly dominated by any particular actors. In other words, the quantitative analysis suggests that in this instance, Twitter as a micro-blogging platform is not primarily an ‘echo chamber’ and not a highly hierarchical network replicating distributions of media power offline.
The qualitative discourse analysis highlighted the multiplicity of nationalist discourses on immigration that individuals in Britain engaged in towards the end of 2013. The majority of ‘lone users’ were simply tweeting mainstream media headlines or redistributing tweets by the influential Twitter users, without additional commentary. Where it was possible to identify discourses related to immigration from the tweet itself and/or from the user descriptions, a greater proportion of tweets represented an anti-immigration discourse than a pro-immigration discourse. The anti-immigration discourses in both the month of October and December were largely similar, but analysis revealed two key differences: a) In October the focus was on illegal immigrants and immigrant in general, while in December the focus shifted specifically to Romanian and Bulgarian immigrants; b) and there was a palpable moral panic in December about what the lifting of restrictions on January 1st 2014 would mean for immigration to the UK.
Our findings suggest that both those who are anti-immigration and those who are pro-immigration are engaged in the discursive construction of the nation on the micro-blogging platform Twitter. However, the anti-immigrant narratives are much more cohesive, indicating that one organisation sets the tone for anti immigrant discourses. While Twitter provides a platform for challenging this exclusive nationalism, the pro-immigration narratives are too diverse and complex to construct a cohesive discourse that promotes an inclusive idea of the British state and Britishness that can challenge the exclusive nationalism of those promoting an anti-immigration stance.
Future work will involve further quantitative and qualitative analysis to explore change in the structure of the retweet network, and the discourses surrounding migration/immigration over time. Drawing on the terms identified in the qualitative results, additional work will focus on the use of advanced textual analysis methods (such as frequency, ‘co-occurrence’ and ‘co-location’ of terms) for recognising patterns in the use of specific terms in either pro- or anti-immigration tweets. It is our aim that a combination of both automated and manual identification of important terms will further assist in identifying discourses, but also key actors in the propagation of information in tweets surrounding this topic.