We identify three gaps that limit the utility and obstruct the progress of computational text
analysis methods (CTAM) for social science research. First, we contend that CTAM …

Topic modeling is a type of text analysis that identifies clusters of co-occurring words, or
latent topics. A challenging step of topic modeling is determining the number of topics to …

Managerial responses to negative reviews could be easily understood as a brand-
safeguarding strategy by firms because negative reviews can damage a company's …

Ephemeral digital trace data can decrease the completeness, reproducibility, and reliability
of social media datasets. Systematic post deletions thus potentially bias the results of …

We propose a rolling version of the Latent Dirichlet Allocation, called RollingLDA. By a
sequential approach, it enables the construction of LDA-based time series of topics that are …

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 …

Delivery robots are increasingly becoming part of our urban landscape. However, the
general public is divided about their presence in public spaces; some welcome their …

Abstract Mathematics education is like many scientific disciplines witnessing an increase in
scientific output. Examining and reviewing every paper in an area in detail are time …

Parliamentary speech reflects many events, changes and developments in society, as well
as sha** them by influencing legislation and public interest. Knowing what topics have …

The media are under increasing pressure by states to adopt a regime-friendly editorial line
in many countries globally, raising the importance of understanding the conditions of …