Methodology

The publication titled “A Longitudinal Approach to the Analysis of Social Media Engagement” examines anger-driven climate-skeptic content during the 2021 German elections. It emphasizes longitudinal models over cross-sectional ones, revealing that anger boosts far-right message sharing while hindering environmentalist posts. Findings also caution against inflated estimates from cross-sectional analysis, stressing the value of longitudinal research for accurate political communication insights.

The Pearson’s r coefficient is the most popular metric of correlation. In the social sciences, researchers not attuned to the nuances of statistics may be tempted to use it every time they need to compute the correlation between variables, including time series. However, several aspects should be considered when applying this method to time series

We have released CooRTweet version 2.0. This version revises the approach, fixes some bugs, and introduces new features. The package and introductory vignette can be found on CRAN: https://cran.r-project.org/web/packages/CooRTweet.

For the Advanced Data Analysis with R course in the University of Vienna’s Master in Communication Science, I created a free online book explaining key R functions and data analysis operations, with a focus on time series analysis. You can find it here: Time Series Analysis With R

Today we have released CooRnet, an R package developed for detecting coordinated link sharing behavior on Facebook and Instagram. Given a list of URLs, the package queries the CrowdTangle API link endpoint and retrieves the Facebook shares performed by public pages, groups and verified accounts, identifying the networks involved in coordinated activity. The basic functions