For the second study, we grouped up to come up with ideas for an interactive media piece. Our group of 3 came up with the idea of a program that pulled Donald Trump’s Twitter feed and censored certain words which considered to be either loaded or controversial. Ideally, we’d allow the audience to select what words are censored, as a take on the theme of censorship, however, this was a bit too difficult to program. The idea that an audience has control over what is and is not politically correct is something that I find interesting. What we react strongly to says quite a lot about who we are.

This idea proved to be quite difficult to actually get up and running.

Firstly, we had to find a way of getting the tweets from Twitter’s server. Originally I had set up a system to send all of the Tweets from a specific page to an RSS feed, which would then be easier to parse into Max using built-in tools. However, luckily for us, Camille found an external object, based on Twitter4j, which made pulling tweets directly from a Twitter search query very easy. The object worked pretty well. However, due to recent changes in Twitter’s character limit, it was only able to pull truncated versions of the tweets (140 char. max). This would’ve been an easy fix for the developer, however, I wasn’t able to find the Twitter API call in the libraries of the addon, so we ended up just using the truncated tweets.

Another issue we faced was analysing each word of the tweet separately. My first thought was to run a ‘foreach loop’, however because of the way Max deals with strings this wasn’t possible. Instead, we used a pack & unpack system, which in some instances left words from previous tweets in the output. We paired this with an external object which analysed an inputted word, this allowed for easier modularisation of the whole process, as we could adjust one object and have all 25 instances updated. This external object system is something I will definitely be using again.

Download the Max Patch here.