Intelligent News Archive with Sentiment and Topic Analysis

Competence CenterInformation Retrieval and Machine Learning
ContactProf. Dr.-Ing. Sahin AlbayrakDanuta Ploch
Partner: Neofonie GmbH


In the INAMET project users are taken on a tour of the past years' events. INAMET analyzes a large number of German news articles with regard to their topic and time of publication. Events such as the Tsunami impact in Fukushima and the catastrophic reactor accident in 2011 for example can be aggregated under the topic “Nuclear energy” and can be connected to the nuclear phase-out debate. In this way, INAMET offers the user a hierarchically structured news overview. Interpreting the news events over time also makes it possible to extract and track opinions and resonance in the media about popular topics, persons or organizations. 

Topic Hierarchy and Opinion Mining

Quotations are of great importance for an opinion analysis of news. INAMET extracts direct and indirect quotations from the masses of daily news articles and finds and analyzes the opinions they contain. A distributed clustering algorithm sorts the recognized events and quotations into topic areas of different levels of abstraction. These topic areas are then arranged in a dynamic hierarchy and presented to the user. This provides users with an overview of the most relevant news topics of different time periods and of how popular opinions on various topics have progressed over time.

INAMET is a cooperation project of DAI-Labor and Neofonie GmbH and is funded by the Federal Ministry of Economics and Technology. 

Online Demonstrator of the INAMET Quotation Extraction system