Filtering Original Signal Into New Noise?

I am very slowly working my way through Harold Jarche’s “Personal Knowledge Mastery” course. Thanks again to my department for fronting the tuition for this online conference. Here is one of the activities Jarche suggests:

Aim #4:
Create a network filter
Activity #4:
You are already following 20-30 people on Twitter from Activity #2. Some of these people may have their own blogs or post links to blogs or other websites. Find 5 of these that you think are interesting. You can bookmark these in your browser and review them from time to time. Another option is to let a feed reader do that for you. An easy web feed reading tool is which will let you subscribe to any website that publishes an RSS (or Atom) feed. If you put the link into Feedly, it will let you know if the site has RSS enabled. For example, my website does.
Using a tool like Feedly lets you organize your information feeds with other social media, as shown in the image below.

So instead of the above suggestion I decided that two tools in Twitter make nice together, Lists and Moments. I don’t know why this combo never occurred to me before, perhaps I have never asked myself serious questions about my filters before.

What I did was to create a List in twitter from my @telliowkuwp account.  I made it as diverse as I could within the limits of time and circumstance and then I created a Moment to filter tweets of interest that I  put under the category “Stuff I Might Never Have Attended to Had I Not Created this Filter”.

Here is an embed of the Moment:

Here is the RSS feed for the List, but I was unable to easily create an RSS feed for the Moment. Here is the link instead.

I think my issue here is to decide how to make sense of the gathering of tweets.  My original filter was very general: what might I have never seen?  Questions are really important filters. I think I am realizing that I don’t know enough about asking useful questions-as-filters.  Need to work on that.

Another filter (or in this case a set of filters) was simply observing different aspects of the Moment. Here is a list of what I observed in each pass:

First pass: I have a bias for images in my tweets. Why?

Second pass: A gender filter–more women that men.  Was I subconsciously trying to counter male bias in my Twitter account?

Third pass: There is a mix of what might be called first order tweets, that is the tweets from those on the original List, and second order tweets, those derived from drilling down into the original List.  This was totally unconscious.  I don’t know what it means.

Fourth pass:  I got my notepad out and characterized each tweet in general terms while also exploring them further.

Lastly, for now, here are the actions I took with each tweet:

1.Labor ‘scab’ story: watch YouTube video.  Yeah, I hate scabs. Verified. Yeah, I love the trash talking they did with the megaphone.

2.International policy story on China:  read tweet, read the re-tweet, looked over image. Image reinforces Chinese foreign policy strategy.

3.Whitewashing in Dear Abby:  skimmed the thread, followed @SikhProf and retweeted his tweet, interesting observation by @arianadelawari  that DearAbby “has a platform,” ran across the interesting phrase, “use your whiteness,” and asked myself if the terms “whitewashing” and “gaslighting” are really the same.

4. Music: I listened to John Cage’s “Williams Mix” for 8 single-track magnetic tape (1952) while reading tweets. Quirky, but inside the notes section was an interesting observation about how the piece was created:

The sounds are in 6 categories: A (city sounds), B (country sounds), C (electronic sounds), D (manually produced sounds), E (wind produced sounds) and F (“small” sounds, which need to be ampified). Pitch, timbre and loudness are notated as well. Approximately 600 recordings are necessary to make a version of the piece. The compositional means were I Ching chance operations.

These are Cage’s filters.  When did he come up with them, before he found the sounds or afterwards? In my case I am filtering after the fact, after I have gathered my material.

5. Soylent, future food in a powerful image: makes the future look real AND scary. 20% of your daily nutrition? NFW!

6. Halloween costume ideas: one from column A and one from column B. A neat filter. We call it a mashup.  I drilled down into the #NPSCostume hashtag. Charming.

7.Radical podcast:  The Guillotine   Provocative.  The opening mashup of Infowars audio is worth the listen.  The rest may not be your cup of tea considering they dox one of the ProudBoys involved in the recent street fight. I like how my filter worked here just like it does in YouTube. I was carried down an even more extreme rabbit hole by wanting to listen to someone really different from me.

8.Decolonization: What does a decolonized digital library look like?  No clue, but I dug down into the hashtag #DLFforum and discovered a very powerful flow chart I would have never seen. (Had to google the image to get untruncated chart.)

9.Vegan racism:  I am in deep and unknown waters here as the connection between vegan radicalism can be tied to vegan racism.  It also led me @ClaireShrugged.  I tweeted to her with thanks and a note that I am following. Grateful.

10. Podcast interview: Linda Nochlin, the ‘first’ feminist art critic, speaks. Mentor, critic, collaborator, surrogate family member. Really fascinating person who I knew zero about. Also, discovered the Art Movements podcast.  Way cool. More deep and grand depths about stuff I am ignorant about.

11. Political podcast:  I live under a hill and in a hollar.  These guys are channeling my country although one is from New Mexico and the other from GodKnowsWhere. I found one of the darkest tweets about the unnecessariat ever tweeted:


‘Nuff said. Their latest podcast is hilariously appalling.

All of this “slow filtering” was inspired by the “Filtering” activity in PKM. Thanks to Harold Jarche for nudging me down this road.  Still not sure what this could mean, not sure how sustainable this activity is, but it sure has been fun to think out loud and with an attitude. Is it the ‘new noise’, a kind of fuzzy, dampened signal?  I reckon. I leave with an incongruity.



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