The Refugee Crisis in Europe on Twitter: A Sentiment Analysis
AbstractSocial networks have started to be the subject of a lot of studies from social scientists. The fact that millions of people write, share and comment is interesting already in itself. Indeed, writing, sharing and commenting are the three essential elements of a conversation.
As such, a conversation provides some interesting information about people's feelings, attitudes and behavior. The main rationale behind analyses based on Twitter relies on "the wisdom of the crowds" effect. The assumption is that the aggregated judgment of several people is often better than the judgement of experts or the smartest forecaster (Hogarth 1978). In this case study, we attempt to map the conversations on Twitter about the European refugee crisis. Not only the data (content of the tweets), but also the metadata are interesting. Indeed, the content allows us to do some sentiment analysis. We can thus map positive and negative comments about the refugees. With the metadata, we can for instance map where the tweets originate based on their latitude and
longitude. We can thus add a spatial dimension to the conversations. We also join a set of different attributes to the data and metadata of the tweets, such as the number of refugees in a country and the routes from their origin country to Europe.