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Arnim Bleier

Publications and source records attributed to Arnim Bleier.

22 records · Page 2Linked to original sources

Author Name Co-Mention Analysis: Testing a Poor Man's Author Co-Citation Analysis Method

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 likely significantly biased coverage of these fields in the standard citation databases. Citations, and especially author citations, play a highly significant role in that literature, however. In this work in progress, we report preliminary methods and results for an author name co-mention analysis of a large fragment of a particularly interesting corpus of German sociology: a quarter century's worth of the full-text proceedings of the Deutsche Gesellschaft fuer Soziologie (DGS), which celebrated its 100th anniversary meeting in 2012. Results are encouraging for this poor cousin of author co-citation analysis, but considerable refinements, especially of the underlying computational infrastructure for full-text analysis, appear advisable for full-scale deployment of this method.

cs.DL↗

When Politicians Tweet: A Study on the Members of the German Federal Diet

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 the likelihood of a politician using replies increases with typical leisure times while retweets occur constant over time. Including formal references increases the probability of a message being retweeted but drops its chance of being replied. This hints to a more professional use for retweets while replies tend to have a personal connotation.

cs.SI↗

Towards an Author-Topic-Term-Model Visualization of 100 Years of German Sociological Society Proceedings

Author co-citation studies employ factor analysis to reduce high-dimensional co-citation matrices to low-dimensional and possibly interpretable factors, but these studies do not use any information from the text bodies of publications. We hypothesise that term frequencies may yield useful information for scientometric analysis. In our work we ask if word features in combination with Bayesian analysis allow well-founded science mapping studies. This work goes back to the roots of Mosteller and Wallace's (1964) statistical text analysis using word frequency features and a Bayesian inference approach, tough with different goals. To answer our research question we (i) introduce a new data set on which the experiments are carried out, (ii) describe the Bayesian model employed for inference and (iii) present first results of the analysis.

cs.DL↗

A simple non-parametric Topic Mixture for Authors and Documents

This article reviews the Author-Topic Model and presents a new non-parametric extension based on the Hierarchical Dirichlet Process. The extension is especially suitable when no prior information about the number of components necessary is available. A blocked Gibbs sampler is described and focus put on staying as close as possible to the original model with only the minimum of theoretical and implementation overhead necessary.

cs.LG↗