scholarly journals Narratives of the Refugee Crisis: A Comparative Study of Mainstream-Media and Twitter

2019 ◽  
Vol 7 (2) ◽  
pp. 275-288 ◽  
Author(s):  
Adina Nerghes ◽  
Ju-Sung Lee

The European refugee crisis received heightened attention at the beginning of September 2015, when images of the drowned child, Aylan Kurdi, surfaced across mainstream and social media. While the flows of displaced persons, especially from the Middle East into Europe, had been ongoing until that date, this event and its coverage sparked a media firestorm. Mainstream-media content plays a major role in shaping discourse about events such as the refugee crisis, while social media’s participatory affordances allow for the narratives to be perpetuated, challenged, and injected with new perspectives. In this study, the perspectives and narratives of the refugee crisis from the mainstream news and Twitter—in the days following Aylan’s death—are compared and contrasted. Themes are extracted through topic modeling (LDA) and reveal how news and Twitter converge and also diverge. We show that in the initial stages of a crisis and following the tragic death of Aylan, public discussion on Twitter was highly positive. Unlike the mainstream-media, Twitter offered an alternative and multifaceted narrative, not bound by geo-politics, raising awareness and calling for solidarity and empathy towards those affected. This study demonstrates how mainstream and social media form a new and complementary media space, where narratives are created and transformed.

2018 ◽  
Vol 4 (3) ◽  
pp. 205630511878563 ◽  
Author(s):  
Ju-Sung Lee ◽  
Adina Nerghes

In recent years, increasing attention has been dedicated to the hazardous and volatile situation in the Middle East, a crisis which has pushed many to flee their countries and seek refuge in neighboring countries or in Europe. In describing or discussing these tragic events, labels such as “European migrant crisis” and “European refugee crisis” started being widely used by the media, politicians, and the online world alike. The use of such labels has the potential to dictate the ways in which displaced people are received and perceived. With this study, we investigate label use in social media (specifically YouTube), the emergent patterns of labeling that can cause further disaffection and tension or elicit sympathy, and the sentiments associated with the different labels. Our findings suggest that migration issues are being framed not only through labels characterizing the crisis but also by their describing the individuals themselves. Using topic modeling and sentiment analysis jointly, our study offers valuable insights into the direction of public sentiment and the nature of discussions surrounding this significant societal crisis, as well as the nature of online opinion sharing. We conclude by proposing a four-dimensional model of label interpretation in relation to sentiment—that accounts for perceived agency, economic cost, permanence, and threat, and identifies threat and agency to be most impactful. This perspective reveals important influential aspects of labels and frames that may shape online public opinion and alter attitudes toward those directly affected by the crisis.


2020 ◽  
Author(s):  
Victoria Yantseva

This study undertakes a systematic analysis of media discourse on migration in Sweden from 2012 to 2019. Using a novel data set consisting of mainstream newspapers, Twitter and forum data, the study answers two questions: What do Swedish media actually talk about when they talk about “migration”? And how do they talk about it? Using a combination of computational text analysis tools, I analyze a shift in the media discourse seen as one of the outcomes of the European refugee crisis in 2015 and try to understand the role of social media in this process. The results of the study indicate that messages on social media generally had negative tonality and suggest that some of the media frames can be attributed to a migration-hostile discourse. At the same time, the analysis of framing and sentiment dynamics provides little evidence for the discourse shift and any long-term effects of the European refugee crisis on the Swedish media discourse. Rather, one can hypothesize that the role of the crisis should be viewed in a broader political and historical context.


2020 ◽  
pp. 224-249
Author(s):  
Philip E. Phillis ◽  
Philip E. Phillis

In the final chapter, the author focuses on the most recent efforts by Greek filmmakers to direct attention to the ongoing refugee crisis. In particular, 4.1 Miles (2016) and Summer on the Island of Good (2009), exhibited online , deal head-on with the plight of refugees in Greece and en route to Europe and simultaneously reveal the indifference of the European community and the difficulties that Greece faces in managing the situation amidst its financial crisis. In addition, Golden Dawn: a Personal Affair/Xrysi Avgi:Prosopiki Ypothesi (2016) sheds light on the alarmingly growing popularity of the neo-Nazi party Golden Dawn which has spearheaded a racist rhetoric and attacks on refugees. The discussion thus focuses on cinema as a means towards raising awareness, to politically engage with endemic xenophobia and to challenge cultural perceptions. Ultimately, this chapter aims to show the potential of Greek cinema to document the plight of refugees in a manner that mainstream media and the political establishment overlook.


Electronics ◽  
2022 ◽  
Vol 11 (2) ◽  
pp. 189
Author(s):  
Álvaro de Pablo ◽  
Oscar Araque ◽  
Carlos A. Iglesias

The analysis of the content of posts written on social media has established an important line of research in recent years. The study of these texts, as well as their relationship with each other and their dependence on the platform on which they are written, enables the behavior analysis of users and their opinions with respect to different domains. In this work, a hybrid machine learning-based system has been developed to classify texts using topic modeling techniques and different word-vector representations, as well as traditional text representations. The system has been trained with ride-hailing posts extracted from Reddit, showing promising performance. Then, the generated models have been tested with data extracted from other sources such as Twitter and Google Play, classifying these texts without retraining any models and thus performing Transfer Learning. The obtained results show that our proposed architecture is effective when performing Transfer Learning from data-rich domains and applying them to other sources.


2020 ◽  
Vol 1 (1-2) ◽  
pp. 127-144
Author(s):  
Paula Jurišić

This article provides a glimpse into the echo of the European refugee crisis in contemporary European cinema and the modes of narration deployed in representations of the phenomenon that is rapidly changing the European political and cultural landscape. The representation of the crisis seems to be bringing about a crisis of representation. Mainstream media refugee images are penetrating both the big screens and television production. Drama and victimhood are, consequently, inevitably becoming the dominant modes of narration (See Rosi’s Fuocoammare), but a growing number of filmmakers address the issue in rather creative ways, bravely experimenting with the nature of the cinematic event as a whole.


Author(s):  
Yujie Wang ◽  
Damminda Alahakoon ◽  
Daswin De Silva

The event-indexing situation models are introduced as event models derived from language to facilitate comprehension and memory retrieval. These models explain how fragmental information about events are collected, integrated and updated into a coherent set of views of what the text is about. The models are adopted as the basis of this study as an attempt to capture the event with contextual, dynamic, and social features, as conveyed by the vast volumes of online textual resources. Information in social media is received through highly personalized channels and is reshaped and interpreted in a more individual, segmental and real-time manner. The reprocessed information is then spread at high speed to a wider range of receivers. Therefore, the interpretation of mainstream media content is influenced by ongoing and dynamic contribution of opinions by users empowered by social media. This new phenomenon has not been examined so far from the perspective of the impact on conventional situation models. This paper explores how collaborative and sharing aspects of social media emphasize subjectivity of interpretation of mainstream media and proposes an extended cognitive situation model which better represents event-centric knowledge. This study investigates the mechanisms for constructing and updating the situation models with continuous textual information streamed from heterogeneous forms of media. It also empirically demonstrates how the proposed model can enhance the understanding of subjective aspects of events with dynamic social opinions.


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