Emotions spread through online and offline social networks and subsequently influence individuals’ decisions and behaviours. Empirical studies on emotional contagion are almost non-existent in infor-mation systems research, leaving a gap in understanding how individuals are affected by emotions ex-pressed in online sources. Online newspaper articles and the associated readers’ comments provide a rich and mostly unfiltered data source that is utilized in this work to identify emotional contagion effects between newspaper publishers and its readers. By applying lexicon-based sentiment analysis and multi-level linear regression models to 1,151 online newspaper articles and 28,948 associated readers' com-ments, we model the relationships between sentiments in newspaper articles and comments. The results provide empirical support for emotional contagion effects between emotions expressed in online news-paper articles and emotions expressed in readers' comments. Linguistic, psychological and methodo-logical limitations are considered and discussed.