twitter filter bubbles

Many educators use Twitter to build their personal learning network and participate in an online community of fellow educators. If we build our networks too narrowly, however, we may be co-creating an over-personalized environment that actually closes us off from new ideas. Our personal learning networks may become "filter bubbles" - and part of the reason for this is the nature of social networks and how platforms for them are built. Some of the filtering that leads to this potential narrowing of perspective is self-inflicted, but some of it is built into the platform itself, which tends to reflect our own interests back to us and also emphasize those things which resonate on social platforms.

Filtering is the whole idea
The whole idea of the Twitter timeline is that it presents a filtered selection of what people are saying on Twitter based on whom you have selected to follow. This filter is one that you, as a Twitter user have explicitly chosen - or have you?

Where do your follows come from?
You've chosen to follow a few people (well, more accurately you follow twitter handles) by making an authentic choice - these are usually people you've met or heard about, or institutions you are interested in. But a fair number of the people, institutions, or bots that you follow may come from other sources

• Twitter recommends some twitter handles to follow explicitly. These appear in the "Who to Follow" pane. How are these selected? They may be followed by handles you follow, have many followers, post many tweets... Twitter has some algorithm that determines, based on a set of signals, who they will recommend to you. So if you take Twitter's recommendations, perhaps part of your network was built with the help of this algorithmic filter.

• You may also choose to follow handles based on re-tweets from your existing network, or maybe by looking at whom handles in your network follow. Here the mechanisms of retweeting and following contribute to your network - these mechanisms amplify certain types of tweets and promote certain types of handles, ones that are more "shareable," which generally are more personal, controversial, or otherwise trigger immediate emotional responses. Retweeting and following (and choosing to display follower lists) are examples of social network mechanisms, designed to increase engagement, but also potentially adding to the coherence (or narrowness) of the your networks and its tendency to amplify socially heightened content.
  
• You may get some followers yourself, some which you might recognise, but most of which you likely don't. There is a temptation to follow-back when you get a follower, so you and someone (or something) else may be mutually re-enforcing your filters by reflecting similar values and interests back to each other. This is a general feature of social networks, a filter that arises from social networks' tendency towards network reciprocity.

Your timeline is not your timeline
Imperfect as your network is, the timeline is an accurate view of what is happening in it, right?

In The Filter Bubble, Eli Pariser describes how Facebook's EdgeRank algorithm selects what appears in your NewsFeed (p 37). He suggests later (p 225) that Twitter is more transparent than Facebook since its timeline is not filtered, but includes "everything everyone you're following says."

That was back in 2011, but in 2015 Twitter started applying filters to the home timeline by default (you can opt out). Twitter documentation suggests that this is largely a quality filter, used to filter out duplicate tweets and bots, but Twitter also sometimes use EdgeRank-like signal evaluation to insert or elevate tweets in the timeline, as they say:

Additionally, when we identify a Tweet, an account to follow, or other content that's popular or relevant, we may add it to your timeline. This means you will sometimes see Tweets from accounts you don't follow. We select each Tweet using a variety of signals, including how popular it is and how people in your network are interacting with it.

And depending on the device you are on, you may get a summarized view of top tweets, again "top" being chosen based on signals which derive mainly from the popularity of the tweeter and the sharing potential of the tweet.

The algorithmic filter (similar to the one that recommends you follow others) that injects and prioritizes tweets in your timeline, and the related filter that curates the "In case you missed" notifications may also contribute to the handles that you choose to include in your follow list, further building your network in specific ways.

So what?
As a platform for educators to share ideas, Twitter sometimes seems as close as we are likely to come to the convivial ideal of a free exchange of ideas from around the world.

However, on Twitter both your network itself (your follows and your followers), and your view of it (your timeline and notifications) are shaped by social tendencies, algorithms, platform mechanics, and emotional responses, along with your own interests, biases, and habits.

Perhaps not an ideal way to get information, ideas, and inspiration, but perhaps still the best available?

References
Pariser, E. (2011). The Filter Bubble: How the New Personalized Web is Changing What We Read and How We Think. New York: Penguin