Algorithms of Predictive Text

In this video that I just created, the reason I use Twitter was that I view a 280 word limit as synonymous with this platform. Generally, most microblogs I have seen are twitter based, and even blog websites reference twitter for quotes from important relevant figures. I think that these generated statements are different from how we normally express ourselves as stating our point in 280 characters can be quite challenging. Considering the brevity that is 280 characters, one has to be precise and concise with their wording. Since I am no expert Twitter user, I was unable to fully convey my thoughts about “What education is not…”. I could not even complete it with hashtag without going over the limit. What I did find interesting was the predictive hashtags that came up when I did try to use them. I wasn’t even trying to use the hashtag #DonCherryisRight but it popped up in my list of options as Twitter does so based on current trends. This made me wonder about other predictive algorithms in the keyboarding aspects of Twitter. Does it Twitter have a similar code when it comes to the words you are presented with for non hashtags? If so, is there an agenda in how words are presented? How does that affect the thought patterns of the general public that is under the impression that they have agency in word choice? Are there words or patterns of words that are avoided in the algorithm in order to steer thoughts in a particular direction? Do these algorithms exist in other keyboarding apps? These ethical questions are similar to that of the attention economy module and how news feeds are selected for our mobile apps. It is scary to think that predictive text technology could affect our freedom of speech. However, when I type on my mobile device without autocorrect and predictive text, I feel completely inefficient and quickly turn it back on in my settings. Ignorance is bliss.