Posts filed under “Learning Bit x Bit”

Facebook Nodes

The facebook nodes project visualizes connections between people who log into the site. The users are repositioned based on node attraction through a spring system within the nodes. The strength of the node attraction is determined by the users’ connections.

The Googler

The googler is a program that represents what it hears via voice transcription in google images. It exists in a space, presenting google results in a somewhat vague format. My hope is that while overhearing conversations, it will respond with google image representations that somehow add context or put an interesting spin on what is being said. If its behavior is unfamiliar, then I want the images to appear serendipitously synced with the conversation.

POS Tagging and Visualization

Update: the following images show the use of certain words referring to war, children/education, and health care in the combined speeches of the last three presidents. The word choices reflect my own biases. Words such as war, terrorists, terror, security, bomb, attack, were grouped into the “military” category, words such as education, children, schools, teachers, […]

N-gram Text Generators

One of the most parsed and scrutinized bodies of text is the presidential address, so it was the first thing that came to mind to try to replicate with text generation. State of the union addresses use a consistent language that is very intentional, and a vocabulary latent with meaning. Because of the repetition of […]

Stop Tokenizer

Based on the following stop words I tokenized obama’s most recent state of the union. Below is a portion of the results. Stop words: (“a”, “an”, “the”,”and”,”.”,”,”,” “,”because”, “why”,”this”,”is”,”of”,”in”,”if”,”that”,”that’s”,”it”,”then”,”than”,”when”, “we”,”as”,”from”,”to”,”our”,”s”,”have”,”they”,”have”,”?”, “all”,”must”,”who”,”you”,”on”,”for”,”may”,”be”,”/”,”\”\'”,”\””,”get”,”are”,”i”,”am”,”not”, “m”,”make”,”makes”,”for”,”into”,”but”,”can”,”only”,”happen”,”don”,”same”,”against”,”nearly”, “entire”,”sure”, “u”, “!”, “was”, “has”, “its”, “through”, “me”, “his”,”once”,”carry”, “anew”,”‘”, “t”,”let”, “us”, “new”, “before”, “come”,”two”, “one”, “ve”, “go”, “8”, “she”, “her”, “he”,”none”,”at”,”been”,”these”,”what”,”up”,”were”,”them”,”some”,”had”, “their”,”do”,”by”,”or”,”re”,”aren”,”so”,”with”,”will”,”my”,”no”,”there”,”here”,”went”, […]