Context What if we could collect the most popular news from absolutely different sources, regions, countries and continents? What if we would do it every day for a… let’s say one month? What we will see? That’s a challenge! With that idea in mind I started preparing this dataset. Content The data contains news from 10/23/2018 to 11/23/2018. Each day I’ve got approximately 3000 new articles on a wide range of topics presented for 24 countries in a Google news aggregator. The dataset is a CSV file with text, date, country and preprocessed sentiment columns. Sentiment column processed with "Syuzhet" package, showing the average of four different sentiment lexicons. Syuzhet incorporates four sentiment lexicons: The default "Syuzhet" lexicon was developed in the Nebraska Literary Lab under the direction of Matthew L. Jockers The "afinn" lexicon was develoepd by Finn Arup Nielsen as the AFINN WORD DATABASE The "bing" lexicon was develoepd by Minqing Hu and Bing Liu as the OPINION LEXICON The "nrc" lexicon was developed by Mohammad, Saif M. and Turney, Peter D. as the NRC EMOTION LEXICON.