Comparative analysis of the hashtags #RefugeesWelcome and #StopRefugees: Tweets mining and examination with the Knime Analytics Platform

Abstract

The current dissertation examines data related to the #RefugeesWelcome and #StopRefugees hashtags. The Twitter data mining is held with the Knime Analytics Platform and regards tweets published during the 2007-2017 period. First, a description of the reasons that led to the refugee issue takes place, as well as of the impact that the massive refugee flows had to the countries of Europe and the US. Following this, there is a reference on the credibility of twitter data and on the twitter audience. Subsequently, there is a presentation of the research findings per each hashtag respectively. The dissertation concludes with a reference to the limitations of the data discovery and recording, as well as with suggestions for future research on the subject.