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.
This post is adapted from an assignment I completed — I thought the project laid out the basic process of data modelling well and had an intuitive application making it easier for people to follow. This example highlights 6 general steps of a data analysis and discusses what kind of elements it would involve.
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.