As a project drags on, my git commit messages get less and less informative

Public school teachers in the United States are often constrained in terms of their ability to express their moral views on issues that a ect their schools, classrooms, students, and teaching practices, but are able to express their ideas, concerns, and frustrations as private citizens using social media. Previously we developed the Tweet Capture and Clustering System (TCCS) in order to explore how teachers use Twitter, looking at word usage among a group of teacher tweeters, and attempting to nd clusters of teachers who have similar patterns of word usage in their tweets. In the work reported here, we look at teacher tweeters across the 12 months of 2016, seeking to understand how the clusters and the words used in these clusters vary from month to month. In this initial look at the dynamics of the system, we see some evidence of word usage changing across the 12-month period. This initial work sug- gests that extending TCCS to have temporal topic tracing as a core capability will be a meaningful addition to of the system.

While public school teachers in the United States may be constrained from expressing opinions about topics re- lating to their jobs in some public venues, Twitter provides a social platform where these teachers can discuss teaching-related issues and moral views as private citizens. In this work, we develop a computational system, Tweet Capture and Clustering System (TCCS), to support exploration of teachers using Twitter. In particular, TCCS looks at the tweets of a group of teacher tweeters and a list of words of interest, and seeks to identify subgroups of these teacher tweeters who have similar word-usage patterns. In the study reported here, we gather tweets from public Twitter accounts of self-identified teachers over an 11-month period. Through the use of TCCS, we have identified five distinct clusters of teacher tweeters, based on their word usage. Three of these five clusters are defined by the use of moral words. We find that the development and application of computational tools and methods, namely TCCS, allows the exploration of complex philosophical topics in public communication about education.

A small, lightweight, system for keeping tack of the books we (the Southern Maine Men’s Book club) have read over the years. It’s a substitute for sites like Google Groups and GoodReads that we used for a while. Built using some very basic JavaScript with jQuery and a few add-ons, like data tables.

After a recording session on one of those large mixing desks, after you’ve twiddled countless knobs and push around many faders you do something called zeroing the desk. This is were you turn every control and push every fader back to zero, so that when the next engineer comes in he or she isn’t going to jump out of their seat when a large sub-bass whacks them straight in the face and possibly blows something up. – Brendan Dawes

Packaging of Scorchworks F-Engrave as an macOS Application. F-Engrave generates ‘GCODE’ for Computer Numerical Control (CNC) systems from text and bitmaps. It “Supports Engraving and V-Carving, Uses CXF and TTF fonts, Imports DXF and Bitmap images”. The official F-Engrave and instructions are at Scorchworks. This fork is merely to add packaging for macOS systems, creating a clickable ‘Application’ that can be installed on any macOS system. This eliminates having to run F-Engrave from a Terminal prompt.

@DorisASantoro and @stephenhouser present Machine Learning and Moral Communities @bowdoincollege faculty lunch #teachertweets