In this article, we analyse how the debate on the ‘refugee crisis’ has been constructed in Finnish news media and social media by using big data analytics. The study applies big data with the aim of exploring the dynamics between the mainstream news media and social media and the ways in which these dynamics shape and strategically amplify different understandings of the refugee crisis. The research highlights over-emphasis of crime and threat-oriented themes on refugee issues in social media, as well as illuminates the distinct role of social media platforms in shaping debates through user practices of hyperlink sharing and networked framing. Together these findings suggest that the hybrid media environment provides a possible arena for polarization of the refugee debate that could also be used for political ends.
AdamicLAGlanceN (2005) The political blogosphere and the 2004 U.S. election: Divided they blog. In: Proceedings of the 3rd international workshop on Link discovery, pp. 36–43.
2.
AletrasNBaldwinTLauJH, et al. (2017)
Evaluating topic representations for exploring document collections.Journal of the Association for Information Science and Technology68(1): 154–167.
3.
BakshyEMessingSAdamicLA (2015)
Exposure to ideologically diverse news and opinion on Facebook.Science348 (6239): 1130–1132.
4.
BennettWLSegerbergA (2012)
The logic of connective action. Information, Communication & Society15(5): 739–768.
BleiDM (2012)
Probabilistic topic models.Communications of the ACM55(4): 77–84.
7.
ChadwickA (2013) The Hybrid Media System: Politics and Power.
Oxford:
Oxford University Press.
8.
ChangJGerrishSWangC, et al. (2009) Reading tea leaves: How humans interpret topic models. In: BengioYSchuurmansDLaffertyJD, et al. (eds) Advances in Neural Information Processing Systems 22.
New York:
Curran Associates, pp. 288–296.
9.
ChouliarakiLGeorgiouM (2017)
Hospitability: The communicative architecture of humanitarian securitization at Europe's borders.Journal of Communication62(2): 159–180.
10.
de VreeseCH (2005)
News framing: Theory and typology. Information Design Journal + Document Design13(1): 51–62.
11.
DiMaggioPNagMBleiD (2013)
Exploiting affinities between topic modeling and the sociological perspective on culture: Application to newspaper coverage of U.S. government arts funding.Poetics41(6): 570–606.
12.
EntmanR (1993)
Framing: Towards clarification of a fractured paradigm.Journal of Communication43(4): 51–58.
FletcherRNielsenRK (2018)
Are people incidentally exposed to news on social media? A comparative analysis.New Media & Society20(7): 2450–2468.
16.
Ghosh R and Asur S (2013) Mining information from heterogeneous sources. A topic modeling approach. In: Proceedings of Mining Data Semantics in Heterogeneous Information Networks Workshop at the 19th ACM SIGKDD (ed. Yang Q and Menczer, F.), 10–14 August 2013, Chicago, USA.
17.
GreussingEBoomgaardenHG (2017)
Shifting the refugee narrative? An automated frame analysis of Europe’s 2015 refugee crisis.Journal of Ethnic and Migration Studies43(11): 1749–1774.
18.
GrimmerJStewartBM (2013)
Text as data: The promise and pitfalls of automatic content analysis methods for political texts.Political Analysis21(3): 267–297.
19.
GuggenheimLJangSMBaeSY, et al. (2015)
The dynamics of issue frame competition in traditional and social media.The Annals of the American Academy of Political and Social Science659(1): 207–224.
20.
HarrisonAC (2016)
Mediations of ‘the refugee crisis’: The (ir)reconciliation of ideological contradictions in Fortress Europe. Networking Knowledge9(4): 1–16.
21.
HolmesSMCastañedaH (2016)
Representing the ‘European refugee crisis’ in Germany and beyond: Deservingness and difference, life and death.American Ethnologist43(1): 12–24.
22.
JacobiCvan AtteveldtWWelbersK (2016)
Quantitative analysis of large amounts of journalistic texts using topic modeling.Digital Journalism4(1): 89–106.
23.
JacobsonSMyungEJohnsonSL (2016)
Open media or echo chamber: The use of links in audience discussions on the Facebook pages of partisan news organizations.Information, Communication & Society19(7): 875–891.
24.
JenkinsHFordSGreenJ (2013) Spreadable Media.
New York:
NYU Press.
25.
LevyKECFranklinM (2013)
Driving regulation: Using topic models to examine political contention in the U.S. trucking industry.Social Science Computer Review32(2): 182–194.
26.
MaierDWaldherrAMiltnerP, et al. (2018)
Exploring issues in a networked public sphere.Social Science Computer Review36(1): 3–20.
27.
MerazS (2011)
The fight for ‘how to think’: Traditional media, social networks, and issue interpretation.Journalism12(1): 107–127.
28.
MerazSPapacharissiZ (2013)
Networked gatekeeping and networked framing on #Egypt.The International Journal of Press/Politics18(2): 138–166.
29.
MorganJSLampeCZubair ShafiqM (2013) Is news sharing on Twitter ideologically biased? In: Proceedings of the 2013 conference on computer supported cooperative work – CSCW ’13. New York: ACM Press, p. 887.
30.
MäkinenK (2016)
Uneasy laughter: Encountering R the anti-immigration debate.Qualitative Research16(5) 541–556.
31.
MöllerJTrillingDHelbergerN, et al. (2018)
Do not blame it on the algorithm: An empirical assessment of multiple recommender systems and their impact on content diversity.Information, Communication & Society21(7): 959–977.
32.
NelimarkkaMLaaksonenS-MSemaanB (2018) Social media is polarized, social media is polarized. In: Proceedings of the 2018 on designing interactive systems conference 2018 – DIS ’18. New York: ACM Press, pp. 957–970.
33.
NikunenK (2015) Politics of irony as emerging sensibility of anti-immigrant debate. In: AndreassenRVitusK (eds) Affectivity and Race: Studies from Nordic Contexts. London: Routledge, pp. 21–42.
34.
PapacharissiZ (2015) Affective Publics: Sentiment, Technology and Politics.
Oxford:
Oxford University Press.
35.
PariserE (2011) The Filter Bubble: What the Internet is Hiding from You.
New York:
Penguin UK.
36.
ReinemannCStanyerJScherrS, et al. (2012)
Hard and soft news: A review of concepts, operationalizations and key findings.Journalism13(2): 221–239.
37.
SiaperaEBoudouridesMLenisS, et al. (2018) Refugees and network publics on Twitter: Networked framing, affect, and capture. Social Media + Society 4: 1–21.
38.
TufekciZ (2014)
Social movements and governments in the digital age: Evaluating a complex landscape.Journal of International Affairs68(1): 1–19.
39.
WallachHMMurrayISalakhutdinovR, et al. (2009) Evaluation methods for topic models. In: Proceedings of the 26th annual international conference on machine learning – ICML ’09. New York: ACM Press, pp. 1–8.
40.
Ylä-AnttilaT (2018)
Populist knowledge: ‘Post-truth’ repertoires of contesting epistemic authorities. European Journal of Cultural and Political Sociology5: 356–388.
41.
ZhouYMoyP (2007)
Parsing framing processes: The interplay between online public opinion and media coverage.Journal of Communication57(1): 79–98.
