Anima Mundi


This bot uses the Opinion Lexicon corpus, a list of around 6500 negative and positive words, available at:

https://www.cs.uic.edu/~liub/FBS/sentiment-analysis.html#lexicon

Anima Mundi is a twitterbot which analyses the twitter feed according to sentiment analysis, then visualises the result.

Sentiment analysis, also known as opinion mining, is commonly used in a commercial context to determine the tone of a piece of text. Bots crawl social media and other websites in order to generate data on the opinions of target audiences for a certain product, which is then subsequently used to influence marketing campaigns.

Whilst the opinion lexicon is not sufficient enough for accurate sentiment analysis, it is a necessary tool and provides some insight into the processes underlying data collection currently in use.

The code of the bot is written using Processing. The code queries the use of negative and positive words in the Twitter feed, then displays a result dependent upon the ratio between the two. The visualisation relates to neuroaesthetic theories on the principles of art, in that the higher positive-to-negative produces a more harmonious, symmetrical, orderly and balanced image, whereas with a higher negative-to-positive ratio the image is more disharmonious, asymmetrical, random and uneven.