Latent Dirichlet allocation (LDA) topic models are increasingly being used in communication research. Yet, questions regarding reliability and validity of the approach have received little attention thus far. In applying LDA to textual data, researchers need to tackle at least four major challenges that affect these criteria: (a) appropriate pre-processing of the text collection; (b) adequate selection of model parameters, including the number of topics to be generated; (c) evaluation of the model's reliability; and (d) the process of validly interpreting the resulting topics. We review the research literature dealing with these questions and propose a methodology that approaches these challenges. Our overall goal is to make LDA topic modeling more accessible to communication researchers and to ensure compliance with disciplinary standards. Consequently, we develop a brief hands-on user guide for applying LDA topic modeling. We demonstrate the value of our approach with empirical data from an ongoing research project.

We have used three beta-thalassemic mutations, IVS2-654, -705 and -745, that create aberrant 5' splice sites (5' ss) and activate a common cryptic 3' ss further upstream in intron 2 of the human beta-globin gene to optimize a generally applicable exon-skipping strategy using antisense derivatives of U7 small nuclear RNA (snRNA). Introducing a modified U7 snRNA gene carrying an antisense sequence against the cryptic 3' ss into cultured cells expressing the mutant beta-globin genes, restored correct beta-globin mRNA splicing for all three mutations, but the efficiency was much weaker for IVS2-654 than for the other mutations. The length of antisense sequence influenced the efficiency with an optimum of approximately 24 nucleotides. Combining two antisense sequences directed against different target sites in intron 2, either on separate antisense RNAs or, even better, on a single U7 snRNA, significantly enhanced the efficiency of splicing correction. One double-target U7 RNA was expressed on stable transformation resulting in permanent and efficient suppression of the IVS2-654 mutation and production of beta-globin. These results suggest that forcing the aberrant exon into a looped secondary structure may strongly promote its exclusion from the mRNA and that this approach may be used generally to induce exon skipping.

This study assesses the potential of topic models coupled with machine translation for comparative communication research across language barriers. From a methodological point of view, the robustness of a combined approach is examined. For this purpose the results of different machine translation services (Google Translate vs. DeepL) as well as methods (full-text vs. term-by-term) are compared. From a substantive point of view, the integratability of the approach into comparative study designs is tested. For this, the online discourses about climate change in Germany, the United Kingdom, and the United States are compared. First, the results show that the approach is relatively robust and second, that integration in comparative study designs is not a problem. It is concluded that this as well as the relatively moderate costs in terms of time and money makes the strategy to couple topic models with machine translation a valuable addition to the toolbox of comparative communication researchers.

We seek to understand the role of the Internet in policy monopolies characterized by a dominant coalition in traditional political venues. In these settings, we identify coalitions and counter-coalitions on the Web and ask how these coalitions differ resource-wise and where these differences come from. To do so, we combine link tracing and quantitative content analysis in the field of climate change in Germany and the United Kingdom. Our results show that online contestation is indeed structured by competing coalitions of climate advocates and skeptics. Moreover, the counter-coalitions of climate skeptics turn out to be the true winners of online communication: they have not only incorporated conservative media as their allies, but also managed to make themselves more visible than climate advocates. This visibility stems from their own link setting activity, which makes climate advocates’ passive online strategy of just ignoring the skeptical camp ineffective.

We study the discursive resonance of online climate skepticism in traditional media in Germany, a country where climate skeptics lack public prestige and thus form a political counter-movement. We thereby differentiate two temporal dynamics: resonance can be continuous or selective, based on the exploitation of specific events. Beyond, we test whether such resonance is higher within the conservative media. We rely on news value theory to shed light on the mechanism facilitating or hindering such resonance and identify three indicators for resonance: frames, positions and actors. Using various computational methods as well as qualitative case studies, we examine the skeptical and traditional media discourses over a period of two years. Our analysis shows that there is no continuous resonance. However, our data reveal selective resonance: skeptics' manage to exploit specific events pushing their frames and positions onto traditional media's agenda. Thereby, conservative media did not give greater resonance to climate skeptical voices whereas they resort to downplaying the issue by allocating less space to it.