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Analyzing Online Comments About Refugees With Qda Miner

Analyzing Online Comments About Refugees With Qda Miner

Immigration, immigrants, and refugees are a popular topic virtually the world these days. It is a topic with wide-ranging points of view and comments are often loaded with emotion.

In the book, Representing the Other in European Media Discourse, Dr. Liisi Laineste, Senior Researcher, Estonian Library Museum, Tartu University contributes Installment 12, “Othering in Estonian Online Discussions well-nigh Refugees.” The installment is the result of an wringer of the 2015 refugee slipperiness in Europe in unrecognized and non-anonymous Estonian public forums. The comments that were studied were focused on a local incident, the setting of a fire at a refugee part-way in Vao in north-eastern Estonia in September of 2015. The study draws conclusions from the news readers’ comments to describe how online forums communicate estranged emotions and opinions well-nigh the Other.

As in many other countries, immigration is a hot sawed-off issue in Estonian. Dr. Laineste’s study addresses emotional, discriminating othering of refugees in online comments that emerged virtually the public discussion of setting fire to the part-way for madhouse seekers in Vao, Estonia. I will show how the Other is placed in the middle of a battleground of opinions where emotions unpeace and viewpoints wilt plane increasingly polarized as a result. I tideway my material as a scholar of digital folklore, combining quantitative and qualitative methods, ranging from statistics-based topic modeling and thematic wringer to a diachronic wringer of recurring folkloric motifs and myths.

Dr. Laineste used QDA Miner to lawmaking 2742 comments from a local site to decide the tonality/emotions of the comments. The categorization system included two major parameters (target/object of the comment, emotional tonality) and was compiled with a cumulative method, updating the system in vibrations with the material. The study moreover used the software’s co-occurrence analyses feature, to pinpoint the prevailing types of sentiments. The study identified five principal types of sentiment: anger, fear, shame, disgust, and compassion.

The study’s conclusions discuss the effect of the Internet, the emotional impact of the refugee question, Othering, and how online liaison contributes to the spread and melding of ideas.