Arnim Bleier

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Assessing political conversations in social media requires a deeper understanding of the underlying practices and styles that drive these conversations. In this paper, we present a computational approach for assessing online conversational practices of political parties. Following a deductive approach, we devise a number of quantitative measures from a(More)
In this preliminary study we compare the characteristics of retweets and replies on more than 350,000 messages collected by following members of the German Federal Diet on Twitter. We find significant differences in the characteristics pointing to distinct types of usages for retweets and replies. Using time series and regression analysis we observe that(More)
As a social science information service for the German language countries, we document research projects, publications, and data in relevant fields. At the same time, we aim to provide well-founded bibliometric studies of these fields. Performing a citation analysis on an area of the German social sciences is, however, a serious challenge given the low and(More)
As more and more people use social media to communicate their view and perception of elections, researchers have increasingly been collecting and analyzing data from social media platforms. Our research focuses on social media communication related to the 2013 election of the German parliament [translation: Bundestagswahl 2013]. We constructed several(More)
There are currently two streams that dominate the research on knowledge federation: The one is the trend towards Linked Data, leading to fine-grained structuring of information that is machine readable; The other is the reuse and co-creation of information that spreads the burden of its creation to the public and enables the availability of large knowledge(More)
In this tutorial, we teach the intuition and the assumptions behind topic models. Topic models explain the co-occurrences of words in documents by extracting sets of semantically related words, called topics. These topics are semantically coherent and can be interpreted by humans. Starting with the most popular topic model, <i>Latent Dirichlet(More)