By focusing on the recent events in the Middle East, that have pushed many to .ee and seek refuge in neighboring countries or in Europe, we investigate dynamics of label use in social media, the emergent pa.erns of labeling that can cause further disa.ection and tension, and the sentiments associated with the di.erent labels. To achieve this, we examine key labels pertaining to the refugee/migrant crisis and their usage in the user comment thread of a highly viewed and informational video of the crisis on YouTube. .e use of labels indicate that migration issues are being framed not only through labels characterizing the crisis but also by their describing the individuals themselves. .e sentiments associated with these labels depart from what one would normally expect; in particular, negative sentiment is a.ached to labels that would otherwise be deemed neutral or positive. Interestingly, both positive and negative labels exhibit increased negativity across time. Using topic modeling and sentiment analysis jointly, we discover that the latent topics of the most positive comments show more overlap than those topics of the most negative comments, which are more focused and partitioned. In terms of sentiment, we find that labels indicating some degree of perceived agency or opportunity, such as 'migrant' or 'immigrant', are embedded in less sympathetic comments than those labels indicating a need to escape war-Torn regions or persecution (e.g., asylum seeker or refugee). Our study o.ers valuable insights into the direction of public sentiment and the nature of discussions surrounding this significant societal event, as well as the nature of online opinion sharing.

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Keywords European refugee crisis, Labels and frames, Sentiment analysis, Social media, Topic modeling
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Conference 8th International International Conference on Social Media and Society, #SMSociety 2017
Lee, J.-S, & Nerghes, A. (Adina). (2017). Labels and sentiment in social media: On the role of perceived agency in online discussions of the refugee crisis. In ACM International Conference Proceeding Series. doi:10.1145/3097286.3097300