RT @news: An analysis of News agency ego networks in a microblogging environment

News agencies regularly use Twitter to publicize and increase readership of their articles. Although substantial research on the spread of news on Twitter exists, there hasn't been much focus on the study of the spread of news articles. In this study, we present an innovative methodology involving weighted ego networks to understand how news agencies propagate news articles using their Twitter handle. We propose a set of measures to compare the propagation process of different news agencies by studying important aspects such as volume, extent of spread, conversion rate, multiplier effect, lifespan, hourly response, and audience participation. Using a dataset of tweets collected over a period of 6 months, we apply our methodology and suggest a framework to help news agencies gauge their performance on social media and also provide critical insights into the phenomenon of news article propagation on Twitter.