MediaGist: A cross-lingual analyser of aggregated news and commentaries

Abstract

We introduce MediaGist, an online system for crosslingual analysis of aggregated news and commentaries based on summarization and sentiment analysis technologies. It is designed to assist journalists to detect and explore news topics, which are controversially reported or discussed in different countries. News articles from current week are clustered separately in currently 5 languages and the clusters are then linked across languages. Sentiment analysis provides a basis to compute controversy scores and summaries help to explore the differences. Recognized entities play an important role in most of the system's modules and provide another way to explore the data. We demonstrate the capabilities of MediaGist by listing highlights from the last week and present a rough evaluation of the system.