Twitter List Curation

Collecting, then Cleaning up a Twitter List

Two weeks of experimentation using IFTTT to build Twitter lists has been very enlightening. Instructions to build the list and preliminary observations are located here: 

Building Twitter Lists Using IFTTT
Building Twitter Lists Using IFTTT pt 2

I'm not going to repeat the details from those posts, but will try to offer the process that led me to collecting, cleaning and acting up on the new lists. 

Starting the Collection 

The instructions for starting the automated lists are covered in the articles above. After a week, the EDTECH1 list was nearly 3800 members an the MOOC2 list is approaching 590. 

Twitter has a 5000 member limit, which is actually a useful feature as we will discuss below.

Cleaning up the List

After the IFTTT recipe has run for several hours and the Twitter list populates, it becomes very clear that some Tweeps don't belong on the list. A simple rule set can speed the clean-up task.  

Spammers, Eggs and Evil Twins

Twitter has plenty of accounts that churn out spam, or the avian variation of spam. They are easy to spot on a list - more than 3-4 consecutive tweets, time to review their profile. My opinion: there is no need to include the noise. Click the gear next to their profile and remove them from the list - immediately. 

Eggs are also an easy decision. If a user hasn't taken the time to choose an avatar, what are the chances they are contributing good content? I read a profile that said... "26 year old programmer..." Must not be a good programmer if they cannot figure out how to upload a picture. Remove. 

Evil Twins are those those accounts that simply re-tweet everything that another account has posted. Sometimes it is an obvious variation "XYS-Sales" vs "XYX-Marketing", and they may even use a similar color-coded avatar. Other times they have a "male" account and a "female" account, or some other profile-targeted avatar. Take your time to review the primary account, but there is no need for the Evil Twins. 

I left a more difficult decision point off of the chart - Tweeps that post in a foreign language. If the goal is to build a list to collect a community, then language should not exclude content. Maybe I'll create a "French MOOC" list since it seems that MOOCs are really popular with French speakers. 

The "Cleaned" List

The clean-up process, for these three problem account types, reduced my list by almost 10%. But, it still does not represent the "best-of-the-best-of-the-best" (borrowing from Will Smith in "Men in Black"). The Twitte stream is clear, real people (ok, mostly-real people) are providing content. Are you ready for the next step?

Good results require discipline and effort. 

The "Curated List"

The original "EDTECH" list was built by hand. Fully curated, strictly filtered, including only those that Tweet on the topic on a regular basis. It is more valuable that the auto-generated list. The EDTECH2 list does provide two key advantages: low effort and high speed. Here is how to leverage both: 

• Let the list fully populate - which may be 5000 users, or it may level off at some lower number - like the #MOOC1 list has done at just under 600 users. 
• Clean the list. 
• Review the remaining profiles and add them to your "curated" list. View the Subscribers, read their profiles, and move that that make sense.
• Who "Subscribed" to your list? They are prime targets to add to your curated list. 

If your list does get to 5000, consider culling 50-100 names and letting the list rebuild. This will help identify new voices on your topic.  

The Bottom Line

The initial collection process is a bit rough, but having a specific goal (keywords and hashtags), experimenting with the IFTTT recipes, and having a process to clean up and curate your lists will pay dividends. Plan, Build, Test, Execute, Learn, then start again. 

~Tot1

Building Twitter Lists with IFTTT pt 2

List Curation - The Human Touch. 

Building the Twitter List using IFTTT was the Easy Part

Link to the previous article with How To instructions. But, what about the results? 

• List launched 10/30/2015 with 0 members
• As of 11/2/2015 - Nearly 2096 members

Success? It depends on your definition. 

The Good

The best result is that 27 people subscribed to the list. 

These are people that are looking at the description, and decide to opt-in and follow the list. Tip: make sure that you include a description that entices the correct audience.

Collecting more than 2000 members in about three days, with minimal intervention is an amazing success. And, I was able to turn off the IFTTT recipes so that the list does not continue grow out of control. 

The Bad

My original list (EDTECH) was manually curated and contains less than 250 members. Building the original list was slow, tedious... nearly painful. But, it is much more targeted, much more specific to the user that I want to track. In fact, I went to EDTECH2 and started pulling members into EDTECH just to improve the signal-to-noise ratio.

The Ugly

You know those people on Twitter that search out hashtags to leverage for self-promotion -- like US Trenders that promise re-tweets? Yes, they get collected here as well. 

When I first reviewed the Tweets from this list several of the worst offenders popped-right up. Dozens of mostly-worthless posts. I immediately removed them from the list, hoping that they have moved on to other hashtags. 

How to remove: 

• Open your list and click on List Members
• Click the gear icon next to the profile
• Click on Add or Remove from Lists
• Uncheck the box

Remember - this is not the same as Blocking. Since the lists are Public, you lose a bit of control on members and their posts. 

The Bottom Line

Managing the list (sorting and editing) is still time consuming.  But building lists via IFTTT works very well under these circumstances: 

1. Your hashtag or search term is very specific
2. Your hashtag or search term is tied to an event with a very short time horizon - like a conference that uses a specific hashtag, or a specific sporting event
3. Your list is simply a "list" so you can follow more than 2000 people - with the advantage of a topic or theme

What I would do differently: 

• Create a separate list for each recipe (each term would get a separate list) - to improve the time needed to filter the members.
• Watch the lists to see which Tweeps and which hashtags are the most beneficial. For example, the #GoOpen tag relates to a different theme than #MOOC. One might be more valuable than the other.
• Manage each list to collect the best members to a list with a similar name and description. 
• Manage the recipes to make this cool process even better. 

~Tot1