(followup to my last post: “Escaping from freedom: the problem of designing for user agency“).

I. Introduction

Twitter is generally presented as a “stream” media model — you dip in and see some sampling of messages from accounts you follow. However, what if you wanted to use it more deliberately, e.g. scanning and analyzing all messages, analyzing the volume and quality of each of your follows’ output, or reading tweets sorted or filtered any way you wanted? What if you want the wide radar and engagement, but more control over the noise?

I believe that technically this *is* possible: and it would be an extremely useful way to combine Twitter’s strengths with the type of user control associated with more “expert” tools like Google Reader, Feedly, or SocialBro. Existing 3rd-party Twitter clients such as TweetDeck had some of these aspects, but the future of most such tools is generally in doubt as Twitter’s prod-dev and API policies evolve.

However, we need to keep building our own tools, or as McLuhan said, they will build us. Today an increasing need is for tools/practices to manage our attention and information, or as Howard Rheingold’s aptly put it, “intelligence dashboards, news radars, and information filters.”

I’ll call that general project:

idara: fIlters, DAshboards, RAdars.

idara: Arabic for “direction, governance”
Swahili for department, ministry.

So for now, let’s envision idara part 1:

II. Twitter Processor: description of capabilities

A) Import / Load Tweets

1. Full home_timeline for specified account, time period (all tweets from all accounts I follow)
2. All favorites, from specified account
3. From CSV file
4. All data fields of Tweet

B) View:

1.  Loaded set of Tweets

C) Manipulate:

1. Sort, by any field
2. Select, cut paste
3. Move
4. Move to top
5. Move to bottom
6. Tag

D) Analyze:

1. Which accounts tweeted most frequently
2. Accounts most often favorited, retweeted
3. Tweets most favorited, retweeted

E) Report

1. Express any set of manipulation/analyze steps in a command
2. Ability to run commands on a schedule, send output to various targets.

F) Visualize:

1. Field of avatars, sized proportional to their tweet volume
2. Tweet frequency by hour of day, day of week

G) Export:

1. To CSV file
2. To bookmarks file format
3. To other managers e.g. Evernote, Diigo

.

III. Implementation

I haven’t investigated this in depth, but I think much of it could actually be relatively simple to implement:

• Import: the Twitter API can be used to pull in all home_timeline and favorites; various libraries exist to do this sort of gathering.
• Viewer: just implements a Twitter-like display, able to read from tweet entries drawn from a CSV file or database.
• Manipulate, analyze, visualize: near-term, just use a spreadsheet.

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IV. Discussion

One might initially think, and Twitter Inc. might like us to believe, that Twitter is all about user agency. After all, we pick who to follow, we say anything we want, you can add or drop anyone anytime, right?

Actually, on closer inspection, many aspects of Twitter’s current design and operation tend to limit user agency., often in ways that most users don’t realize. We can imagine a quite different architecture, designed for much greater user control and curation; and to some extent it may be possible to implement it by hacking together some new user tools.

The reason this matters, I believe, is that in key areas we are drifting towards a communications environment governed opaquely and algorithmically by others. We are being encouraged to think the information environment is so complex that we have to relinquish our control over it, and accept the mediation of usually commercial services to manage it for us. We are assumed and encouraged to operate in a state of what Douglass Rushkoff calls “presentism,” assuming that what’s important is what happened most recently and with the most people’s attention. We are offered a “stream” view of media, letting us dip in for somewhat arbitrary samplings, but not much facilitating our curation or agency.

I’d like to demonstrate that the user experience which Twitter, for example, seems to be evolving towards is neither user-centered nor inevitable, but the result of design choices. Another design is possible.