Conceptual Tarleton

I came across a talk by Tarleton Gillespie on soundcloud. My intention was edit the talk down to various clips, remix them and then insert my own interjections to make it appear like I was interviewing Tarleton in my own podcast.

The purpose of this was to experiment with different ways of engaging with the course material. To do re-edit the Tarleton talk I needed to listen carefully through the 2 hours of material and identify key ideas or phrases that could be lifted out of context but still be understood fully. This process struck me as being very similar to notetaking critically, particularly as I was always trying to think how could I phrase a question that would lead into Tarleton’s statement. It would also showcase my burgeoning digital literacy, specifically my ability to remix and repurpose digital materials to my own ends.

Sadly, my laptop crashes every time I try and load up the 2 hours mp3 in Ableton. I tried using Audacity but as I am not familiar with the software I found myself getting increasingly frustrated. Given that the final stage of the process is mainly based around clicking and editing rather than critically engaging with the course materials, I’ve judged it to not be worth my study time to see it through to completion. Instead I leave my notes below. It annoys me to leave a good idea unfinished but instead I am trying to think of it as a piece of concept art. The engagement and critique is more important than the actual execution.


In the previous review section I used some terms like patterns of inclusion that I had picked up from Tarleton Gillespie’s paper on Algorithmic Cultures. I am delight to announce that I have Professor Gillespie here on the show today as a special guest. Tarleton is a Professor of Information Science and Communication at Cornell University and is currently the principal researcher for Microsoft Research. One his many areas of research is algorithmic cultures. So Tarleton what have you been looking at recently?

1.02 – 1.08 nestling

OK that does sound interesting. So algorithms are becoming part of social landscape. What kind of questions does that raise for you?

1.21 – 1.40 systems like fb….

Ah. So you are focusing in on how algorithms are used to present particular bits of information to us and in doing so how that impacts on public consciousness. Can you tell us a bit more about what you mean about shaping public discourse.

2.14 what does it mean

For me that raises many other questions such as

2.38 do we need expertise then what question interests you most?

Yes, thank you. Just go ahead and interject whenever I am talking, I don’t mind at all.


So, this subject seems to be very now, very zietgiest-y. But is it really? Can you give us any examples of any historical precedents for these debates on how information is mediated?

34.02 maybe for a century… we’ve been prepped for information collection over the last century

26.50 we only get so far if we think about it as a 5 year thing, it might that a historical

27.49 search engines are like news editors

Fascinating. Sadly this is an audio only podcast so people can’t see me stroking my chin in thought. But believe me I am. Furiously.


So one of your primary claims is that algorithms are socially significant enough that they are resulting in what you have termed calculated publics. Can you expand on that?

23.50 – 24.38 – calculated publics summary

44.50 to 46 – relevancy and the Bieber problem

50.35 gaming trends, turn towards the measure see also 57.40 see also 1h18m49s

50.55 people act on trends

1h9.40s I’m interested in how twitter presents info to people

1h.10m30s impact of trends on politics, buzzfeed building information economy on trends.


If algorithms are significantly shaping public discourse as you suggest we need to be asking which social actors have privileged access to the data they produce

31.40 – who has the power to collect the data?

Some organisations can compel us to give up data, others have to entice others.

32.40 – companies that can’t compel have to do things differently.

33.17 relating the concept to contemporary social media


So these companies that own the most widely used algorithms, twitter, google, facebook, etc. How do they portray their use of algorithms and their impacts on culture?

46.20 who can produce them and how do they claim authority

19.25 we have the data, we can tell you about yourself

20.44 glimpses of public concern. Snapshots

48 – the algorithm offers impartiality claim

23.18 – 23.30 networks want it both ways

1hr 2m – should designers for algos be responsible for what comes out? Major platforms they want it both ways

1h7m40s twitter says they know things but they are not prepared to accept other responsibilities.

1hr 5m 50s its OK cos the algorithm argument will break down









Why do we have trending alogirthms in twitter

Stay on the site 7.15

10.20 why do you think it is interesting? Technicities of attention.

Treat it as legible.


13.20 – his own questions.


13.50 – summary of trending algorithms

16.30 spreading into our cultural vocabulary, scholarly journals

19.01 activity as importance

22.50 – 23.18 trending is an oblique catograry


25.10 – why do you call them calculated

26.20 – 26.40 what does trending mean to people?

35.40 – twitter is buying datahoses

35.51 – what gets left out of the measurements

39.56 – the claims of trends. It is everyone (?)

40.40 – what is it that twitter is actually measuring? – 43.46

54.12 – what needs to trends satisfy?

55.40 grasp?

56.20 – twitter measures cross cultural measures has an underlying belief system

58.30 – problems with language, reducing things to hashtags

59.35 why should surging be important, also 1hr 10s