TeCoMiner: Topic Discovery Through Term Community Detection
This is an incremental contribution providing a new tool for researchers analyzing text data, with a specific focus on policy-related environmental news.
The authors introduced TeCoMiner, an interactive tool for topic discovery in text collections that uses term community detection in co-occurrence networks instead of generative probabilistic models, and demonstrated its application on a corpus of environmental policy news from the European Commission.
This note is a short description of TeCoMiner, an interactive tool for exploring the topic content of text collections. Unlike other topic modeling tools, TeCoMiner is not based on some generative probabilistic model but on topological considerations about co-occurrence networks of terms. We outline the methods used for identifying topics, describe the features of the tool, and sketch an application, using a corpus of policy related scientific news on environmental issues published by the European Commission over the last decade.