Computational methods, in particular text‐as‐data or Natural Language Processing (NLP)
approaches, have become popular to study climate change communication as a global and …

Supervised machine learning is an increasingly popular tool for analyzing large political text
corpora. The main disadvantage of supervised machine learning is the need for thousands …

Large Language Models (LLMs) have emerged as powerful generative Artificial Intelligence
solutions. This paper presents results and reflections of an experiment done with the LLM …

Topic modeling is a well-established technique for exploring text corpora. Conventional
topic models (eg, LDA) represent topics as bags of words that often require" reading the tea …

Topic modeling has become an effective tool for communication scholars to explore large
amounts of texts. However, empirical studies applying topic modeling often face the critical …

The empirical identification of frames drawing on automated text analysis has been
discussed intensely with regard to the validity of measurements. Adding to an evolving …

Established approaches to analyze multilingual text corpora require either a duplication of
analysts' efforts or high-quality machine translation (MT). In this paper, I argue that …

Advances in analytical methodologies and an avalanche of digitized data have opened new
avenues for (digital) journalism research—and with it, new challenges. One of these …

Scholars have access to a rich source of political discourse via social media. Although
computational approaches to understand this communication are being used, they tend to …

Large Language Models (LLMs) have emerged as powerful generative Artificial Intelligence
solutions which can be applied to several fields and areas of work. This paper presents …