Knowledge discovery from large data collection is increasingly important for knowledge-intensive information systems. In addition, effective visualisation are vital for understanding the knowledge embedded in the data. This paper aims to identify specific named entities from structured text content and visualise them in terms of social relations and geographical locations. The system presented here retrieves author information from publication data, disambiguates people names and creates a graph that visualises the co-author connections in order to build co-author networks for a specified topic in a given time period. Each co-author connection at a different time is shown using a coloured line to effectively visualise the co-author relations over time. The system also retrieves addresses of organizations for authors and displays them on a geographical map. Thus, the places that concentrate on a specific research topic for a given time period are geographically identfied. The paper presents an effective way to discover and visualise social networks of authors and geographical locations of researchers on a particular topic.