When creating artwork I usually have to make custom tools, these tools are often quite useful, as they are designed specifically by me for a task that is usually strange or perhaps where the solution is not as readily available online. They include tools to help analyse metadata and language as well as more visual solutions to help the creation of generative art.
I've been asked multiple times about how I go about creating these tools and whether I would make them open source so now, one by one I will be making them open source and adding them to my python module 'stormkit'.
First is my multiple mood sentiment analysis based on the 'bag of words' model. This class is created for two purposes, to extract the degree of multiple emotions from text (currently positivity, negativity, anger, worry, sadness and scare) and to do this in a lightweight and fast manor, allowing large computations of small text (e.g. tweets) at significantly fast speeds. It's a great class that is at the heart of both "The Watsons, 2016" and "A.M.I, 2017". It's also incredibly simple to use.
stormkit is written in python and can be installed easily with pip, alternativly the git repo for the module is here. To install with pip simply run:
To initiate the class call
To analyse a string call the function analyse_text(), this will return a 'SentimentResult' object
To check if any errors occurred simply check the error variable, this should be done whenever creating a new 'SentimentResult' object
To get the results of the sentiment analysis use one of the following