This project is an attempt to visually model groups of chapters in the Quran. Verse translation texts are analyzed using NLP topic-modelling techniques and then visualization using a specific art concept of Stefanie Posavec’s Sentence Drawings.
Automatic topic-modelling and generation of 'wiring' drawings based on user's tweet history.
Twiring comes from Twitter+Wiring — because these diagrams look like ‘wiring’ diagrams. but also, twiring is to To glance shyly or slyly and that’s precisely the functionality of this form of visualization.
A recent article, critiquing modern literary theory, brought up some questions for readers of my kind - i.e. those who read primarily for pleasure. While academia may have a certain viewpoint of what literary theory should behave like, I wonder if that same criteria bleeds over to the amateur reader? I'll quote parts of the article below and question the assumptions.
A Web App (Python-Flask) that recommends you songs from pre-set playlists based on lyrical lexical qualities. Input a song you like or a block of text and I will recommend you a playlist, show you some fancy graphs, and let you automatically create a Spotify playlist!
A Natural Language Processing (NLP) approach to automatically detect connections through key entities and ideas across articles/documents. I analyzed a set of philosophy articles to see which Entities related them to each other and if this could guide our choice of reading.
A NLP Sentiment Analysis across chapters of a novel (The Catcher in the Rye) to capture patterns and trends as an enhancement to literary analysis. Used IBM's Bluemix and Watson APIs and wrote an essay on the pros/cons of this approach.