I gave a short presentation about ReflectR during the Lace SoLAR Flare event about “ReflectR – Analysing reflective thinking in texts” on Friday 24 October 2014.
In my presentation I talked about ReflectR, an application of reflection detection. Reflection detection analyses text in order to find evidences of reflection. In my PhD research I explored several methods in order to understand to which extend it is possible to automatically classify sentences whether they are reflective or not. The aim is to find reflective sentences in a given text, for example in forum posts or essays.
How does it work? You need a large corpus of labelled sentence. This training corpus is then used to built predictive models which can be used to classify unseen sentences. In my case I created a large corpus of reflective and non-reflective/descriptive sentences. Based on this corpus I was able to tune models which perform well on the testing data. These models can be used to classify nascent text.
To make this idea more graspable I built a little tool called ReflectR in one of my free weekends. ReflectR takes as input a sentence – any sentence written in English. It then processes this sentence, classifies it and returns a value, which is translated into a human readable result. It will tell you if the sentence is reflective and how confident it is with the classification. Try out ReflectR at http://qone.eu/reflectr.
Here is the one page slide for this presentation showing an example sentence, which is automatically processed and classified as reflective. Dewey is greeting.
I see ReflectR as an application of the base technology reflection detection. It is probably not the best application of this base technology, but this is also not its aim. ReflectR was build so that other people can try it and get an idea what reflection detection is about. I am hoping to find people who are interested in reflective thinking and want to collaborate on innovative applications based on reflection detection.