The Thing-onna-stick is a slow data luminaire that derives its shifting patterns of colour from a geo-fenced Twitter feed, via a sentiment analysis algorithm that fuses Finn Årup Nielsen's AFINN-111 dataset and VADER (Valence Aware Dictionary for Sentiment Reasoning), both of which are lexicon-based sentiment analysis algorithms.
The electronic hardware is concealed within a Tasmanian oak post, with an RGB LED strip exposed on one side to allow the coloured light to either rake across a surface that it stands against, or to diffuse itself into the environment.
By transducing the sentiment scores into owner-customisable colours, the Thing-onna-stick is meant to allow further curation of one's desired data stream, and how it is to be presented depending on where the Thing-onna-stick is used.
Part of the rationale behind this work is also to acknowledge the biases that are inherent in the lexicons. Like the Happiness Index, the issues related to the authenticity of data processing algorithms are part of salient and pressing conversations we need to have as we engage with ever-deeper engagements with machine learning.
Work continues on the Thing-onna-stick towards enabling a slow data practice for the public and creative practitioners.