Elevator Pitch
In this workshop we will demonstrate how you can generate insight and new ideas using any textual data. We will show how network representation of a text and its main topics can be used to get a visual overview of your data and how to identify structural gaps to generate insight and new ideas.
Description
In this workshop we will demonstrate how to use text network analysis for topic modeling, finding new relations between the different topics, and identifying the structural gaps in your knowledge to generate new ideas.
We will use open-source text network visualization and analysis tool InfraNodus that runs on top of Neo4J and Node.Js, so we encourage the participants to install it on their computer before the workshop.
In this workshop we will present the specific graph analysis techniques used to analyze the textual data as well as the technical backend of InfraNodus tool for those who are interested in how it works, including the challenges we ecountered building this software.
While we will provide some test datasets, you can bring a short text (1000-2000) characters describing your own field of interest or research, so you can use it to generate insight that will be relevant to your own work.
Notes
During our time working on InfraNodus I conducted multiple webcasts and workshops where I taught different aspects of network analysis, so I know how to explain it both to beginners and experts in a way that will be interesting for everyone, no matter their technical level.
I also want to combine the information about our approach with the technical information about the way our software is written, which will demonstrate to the participants how the tool is built from the ground up: starting from Neo4J data model used to the actual user interface and libraries we use in this work.