Following on from yesterday’s update on my quest to track science influence on Twitter, I’ve posted a bubble-chart of the August “influence stats” for all 523 scientwists in David Bradley’s list over at Many Eyes.

Using the chart, you can quickly explore the number of followers, secondary followers, social capital and a handful of other Twitter stats on the scientwists.

The chart draws on data that Mike Chelen kindly compiled using Twinfluence.

So how do you navigate around these bubble charts, and what do they show?  Here’s a quick tutorial.  (for the adventurous, you can dive straight in here)…

Getting started

First, open this link to the bubble chart at Many Eyes.  The chart on the screen shows “bubbles” representing the number of followers each scientwist has.

Open the bubble chart at Many Eyes, and select "username" from the Color menu

From the “Color” menu at the bottom right of the screen, select “Username”

The screen will now look like the screenshot above, with the scientwists listed to the left of the screen.

Finding specific scientwists

To highlight a particular scientwist, either select them from the list to the left of the screen, or type their name in the search box:

Use the menu on the left or the search box to find specific scientwists

Placing the mouse over the scientwists bubble provides more information on the information being displayed.

To get back to the normal display, either click in the white space surrounding the bubble chart, or clear the search box and hit “Enter”

Showing the number of friends each scientwist has

From the “Bubble Size” menu (bottom left) select “friends_count”.  The bubble chart now shows bubbles with areas that represent the number of people each scientwist is following.  To see the data associated with any bubble, simply position the mouse over it.

To see how many people each scientwist is following, select "friend_count" from the Bubble Size menu

Showing second order followers, social capital, and other stats

Simply select the information you want to see from the Bubble Size menu.  As well as second order followers and social capital, there are a few stats that Twinfluence provides.

Choose the info you are interested in from the Bubble Size menu

Why the bubble charts?

As well as being visually attractive (I’m revealing my shallowness here), the bubble charts at Many Eyes have a couple of advantages in displaying data like these:

• Because the data are represented in two dimensions (area) rather than one (bar height, for instance) it’s a lot easier to compare large and small numbers.  for instance, @guardiantech has over 200 times more followers than @2020science.  On a linear plot, you wouldn’t be able to see @2020science – using the bubbles, where area represents the data – you can see both scientwists together.
• As the bubbles are displayed in two dimensions, it becomes easier to spot interesting patterns and associations.

And finally…

These data were collected by @MikeChelen using an API he wrote specifically to gather large amounts of information from Twinfluence.  And while we’ve used this technique here to look at scientwists, I suspect that it could also be used to great effect to examine other groups of twitter users.

]]> http://2020science.org/2009/08/24/visualizing_scientwists_aug09/feed/ 0 http://2020science.org/2009/08/23/science-influence-on-twitter-august-update/ http://2020science.org/2009/08/23/science-influence-on-twitter-august-update/#comments Sun, 23 Aug 2009 22:38:25 +0000 Andrew Maynard http://2020science.org/?p=2066

It’s the middle of August, and time for my regular two-monthly update on science tweep influence on Twitter.

Back in April I posted data on three indicators of “influence” for ~400 science-focused Twitter users – based on David Bradley’s list of “Scientific Twitter Friends.” This is the third update of the indicators – the second was back in June.  This time round, Mike Chelen (@MikeChelen) was kind enough to put together an application that grabbed the data directly from Twinfluence.

As usual, I’ve posted the data on Many Eyes to allow you to play around with it, and get a better feel for how these indicators vary with person and time.  This time round though, there are separate bubble charts for primary followers, second order followers and social capital (follow the links, and select the data for August – the charts default to the April data).  If you get lost, check out the screencast on navigating the bubble charts in the June update.

Not a whole lot has changed since June.

Number of SciTweeps (vertical) versus number of followers (horizontal). Watch out for the logarithmic x-axis!

The modal number of followers per SciTweep has dropped a little, but overall the distribution of followers per SciTweep hasn’t shifted too much.

Number of SciTweeps (vertical) versus number of secondary followers (horizontal). Watch out for the logarithmic x-axis!

Perhaps the most obvious change is in the distribution of secondary followers amongst SciTweeps.  This has shifted to the right slightly overall, but there are fewer SciTweeps with large numbers of secondary followers.  Either some tweeps with mega-followings have been dropping SciTweeps from the people they follow, or the figures reflect a re-alignment within Twitter that has impacted the data.  Either way, my number of second order followers was hit badly over the past couple of months!

Number of SciTweeps (vertical) versus social capital (horizontal). Watch the logarithmic x-axis!

The range of SciTweep social capital values has narrowed over the past couple of months – more people with a higher social capital, but fewer with a mega-high social capital.

And that’s pretty much it for now.  The plan is to have another update in October, although I may also ask for suggestions on a better way to track SciTweep influence over the long term – including thoughts on putting together a more representative group of tweeps to follow.

Notes:

The data shown here are derived using Twinfluence.  The August data were collected by Mike Chelen.

Where the number of second order followers topped out on Twinfluence, it was capped at 20,000,000 in April, and 30,000,000 in June.

My thanks to David Bradley for compiling the list of “Scientific Twitter Friends” in the first place.  This is largely a self-selected list of science-types on Twitter, and in no way represents the full scientific community there.  But it does provide a highly useful cohort of people who profess to have a science-perspective, and can be tracked over time.  This series of analyses uses the list as it stood mid-April.  To preserve the group, I haven’t added new SciTweeps from David’s list.

A quick word on the plots:  These are a rather crude way of presenting the data, but provide a good qualitative indication of distributions and trends.  The number of science Tweeps represented by each step in the plots represents the Tweeps with primary followers, secondart followers or social capital lying within the range of the step.  As the horizontal axis uses a logarithmic scale, the range of values covered by the steps increases dramatically going from left to right.  As the data are roughly logarithmically distributed, this makes visualizing, comparing and analyzing the numbers easier.  But care should be taken when interpreting the plots, given the logarithmically compressed horizontal axis.  In particular, modal values are dependent in part on the use of a log-axis, and would be different if the data were plotted with a linear horizontal axis.

Back in April I posted data on three indicators of “influence” for ~400 science-focused Twitter users – based on David Bradley’s list of “Scientific Twitter Friends.” Intrigued to see how these Tweeps’ influence evolves over time, I will be updating these data periodically.

In this first update (aided and abetted by @ruthseeley – thanks Ruth!), the overall number of followers (both primary and secondary) of the SciTweep cohort has increased over the past two months – as would be expected given increasing interest in Twitter.  There is the slightest hint of an increase in overall Social Capital. But this is marginal, suggesting that SciTweeps are not deviating substantially from Twitter-wide trends in increasing followers.

These data are available on Many Eyes to play around with (see the screencast below for tips on how to mess around with the bubble chart).  You can even download the original data here and dive deeper into it…

The dataset is reasonably large and no doubt holds a multitude of insights for those dedicated to mining it (although with only two date points, it is still lacking in depth).  But rather than go into deep analysis here, I thought I would restrain myself and simply focus on the distribution of the three indicators amongst the group, and changes over the past two months. (Details on the three indicators of “influence” are covered in the April SciTweet blog).

In looking at these figures, please bear in mind that the group of ~400 Tweeps is one of convenience – it does not represent all current science Tweeps, and indeed overlooks some key figures in the Twitter community.  But for the purpose of following a group of science-focused Twitter users over time, it serves its purpose well.

Number of SciTweeps (vertical) versus number of followers (horizontal). Watch out for the logarithmic x-axis!

Looking at SciTweep followers, there has been a shift in the modal number of followers from 133 in April to 422 in June – although these figures are approximate given the step-size used.  Clearly though, there’s been an increase in the number of people following most of our SciTweets.

Number of SciTweeps (vertical) versus number of secondary followers (horizontal). Watch out for the logarithmic x-axis!

There has been an overall increase in secondary followers over the past two months, although not sufficient to lead to a definite increase in modal value in the plot above.

Number of SciTweeps (vertical) versus social capital (horizontal). Watch the logarithmic x-axis!

The social capital distribution has barely shifted over the past two months.  As this is based on the ratio of a SciTweep’s secondary to primary followers, it provides a measure of how the SciTweeps are faring compared to the rest of Twitterdom.  A significant shift to the left or right would suggest the cohort of science Tweets loosing or gaining influence compared to other Tweeps.  Given the similarity between the two distributions above though, it seems that the SciTweeps are holding their own, but not showing appreciably different changes in influence compared to other tweeps.

Finally, I thought it worth posting a quick screencast of how to navigate round the bubble charts on Many Eyes.  Enjoy:

Update 6/23/09:  Bubble Charts updated with correct data for @maverickny (formerly – and erroneously – listed as @maverick_NY)

Notes:

The data shown here are derived using Twinfluence.

Where the number of second order followers topped out on Twinfluence, it was capped at 30,000,000

My thanks to David Bradley for compiling the list of “Scientific Twitter Friends” in the first place.  This is largely a self-selected list of science-types on Twitter, and in no way represents the full scientific community there.  But it does provide a highly useful cohort of people who profess to have a science-perspective, and can be tracked over time.  This series of analyses uses the list as it stood mid-April.

A quick word on the plots:  These are a rather crude way of presenting the data, but provide a good qualitative indication of distributions and trends.  The number of science Tweeps represented by each step in the plots represents the Tweeps with primary followers, secondart followers or social capital lying within the range of the step.  As the horizontal axis uses a logarithmic scale, the range of values covered by the steps increases dramatically going from left to right.  As the data are roughly logarithmically distributed, this makes visualizing, comparing and analyzing the numbers easier.  But care should be taken when interpreting the plots, given the logarithmically compressed horizontal axis.  In particular, modal values are dependent in part on the use of a log-axis, and would be different if the data were plotted with a linear horizontal axis.

And finally, many thanks to @ruthseeley for help in running SciTweeps through Twinfluence – a finger-numbing task!

]]> http://2020science.org/2009/06/23/science-influence-on-twitter-june-update/feed/ 16 http://2020science.org/2009/06/03/to-tweet-or-not-to-tweet/ http://2020science.org/2009/06/03/to-tweet-or-not-to-tweet/#comments Wed, 03 Jun 2009 22:58:55 +0000 Andrew Maynard http://2020science.org/?p=1696

Should live tweeting and blogging from scientific meetings be controlled?

Back in May, Daniel MacArthur – a researcher and blogger – wrote a number of on-the-spot blogs on the Cold Spring Harbor Laboratory (CSHL) Biology of Genomes meeting.  By all accounts a number of people were tweeting and blogging from the meeting.  But Daniel had the misfortune to come under scrutiny from Genomeweb – a web-based news service – because of his actions. As ScienceInsider reported yesterday, Genomeweb complained to the conference organizers that Daniel was reporting from the meeting without having to abide by the rules governing professional journalists attending the conference.  As a result, the rules are being changed – according to ScienceInsider, the meeting’s registration form will be revised “such that all participants will agree that if they are going to blog or twitter results, they need to let CSHL know in advance and get the presenter’s okay.”

Judging by discussions on the web today, the story has hit a nerve.  More importantly, it has raised a thorny issue that really needs to be tackled as the way people communicate changes: 

What’s OK and what’s not when you’re at a scientific meeting?

As a blogger and Twitter user, as well as a regular speaker at scientific meetings, it’s a question that is directly relevant to me.  Reading the discussions today and talking with people on Twitter about the issue, I was forced to think a little more carefully about how I make decisions on when to tweet or blog, and when not to…

I do have my own set of rather fuzzy internal guidelines, but I’ve never attempted anything as formal as writing them down.  However, given the rising significance of this issue, I thought it might be worth thinking through them a little more systematically.

I’m still trying to work out what the appropriate boundaries are here, so what you are getting is more my current thought processes than any definitive answers – think of it as live -logging from my brain.  As a consequence, I could well change my mind – completely – at some future date.  But this is where I am at the moment.

First off, it’s worth thinking about why people blog or tweet, what the purpose of scientific meetings is, and the role of the established media at these meetings.

Blogging and tweeting: Are bloggers and tweeps citizen-journalists?  I don’t think we are on the whole.  Certainly, some people use blogs and Twitter to report on events.  But many others simply use the media as a way of communicating their own thoughts, observations and reactions to others. This is not journalism.

My own stuff is a mix of expert opinion, observations on stuff that grabs my interest, and occasionally factual information that I think others will be interested in.  I don’t “report” – I’m not a reporter, and I couldn’t hope to do it with nearly the skill of someone having the appropriate training.

There is a potential problem though when social media commentators – which is what a lot of us are I guess – are treated as reporters, and the stuff we write is judged accordingly.  However, placing the same code of ethics and restrictions on bloggers and Twitter users as professional journalists makes little sense – the problem is not one of what is being written as how it is being read.  Rather, new solutions are needed to the new challenges raused by social media.

Scientific meetings: Scientific meetings come in all shapes and sizes.  Some are invitation only; others are open and accessible to anyone.  Some are designed to hash out areas of uncertainty between experts; others to present results to a broad audience.  Some are held to expose research to rigorous peer review; others to establish scientific authority.  Acceptable reporting practices will undoubtedly differ from meeting to meeting.  I would be very surprised if anyone thought that live-tweeting from a private meeting was acceptable.  But a running commentary on a public keynote given by established expert would be a very different matter in my eyes.

Scientific meetings and the media: Once upon a time, scientific conferences were predominantly about exchanging and examining new information with your peers – at least, they were in my field of research.  Reporters just weren’t a part of the equation.  Now, major conferences tend to be a media-fest – with the scientific community clamoring to have their messages and stories heard by all and sundry.  There’s tremendous pressure to “sell” studies to the media – to work out what might appeal to a broad readership, then dress it up so it’s as attractive as possible.  If you don’t believe me, just take a look at the press releases and media coverage surrounding something like an American Chemical Society meeting.

As a result there is a tendency – at some conferences at least – for presentations to be less about peer to peer review and discussion, and more about broad dissemination and promotion.  In this context, people want their work to be communicated in the media – but on their terms.  In other words, they love the media when they feel they are on control, but get antsy if they feel that control slipping.

Trying to pull this together, it seems clear that as social media stretches and challenges the established way of doing things, there’s going to have to be some adjustment on both sides.  I think it’s fair to say that there are probably boundaries to appropriate live-tweeting and blogging that still need to be hashed out.  But conference organizers and speakers also need to adapt to changing circumstances.  And I don’t think that this means treating citizen commentators as journalists.  But I do think that, among other things, it means shedding attitudes that treat the media – social or otherwise – as something to be controlled and used, rather than worked in partnership with.

Which brings me to how I approach tweeting and blogging.  I’ve live-tweeted from meetings in the past, as well as blogged on meetings.  I have also made conscious decisions not to comment in any form on meetings on occasions.  I don’t think I have got it right in every case.  But I haven’t had too many complaints either.  So how do I determine what I do and don’t do?

Here’s a first stab at trying to describe my decision-making process:

In general: Irrespective of the setting, I tend to ask whether the information being presented is confidential, whether it is sensitive in any way, and whether others would benefit from reading about it on Twitter or 2020science. There has been at least one occasion where I decided not to live-tweet from a public meeting because I thought it would embarrass the speakers unnecessarily.  There have been other occasions where I have live tweeted to provide people not at the meeting a sense of what someone is saying, as they say it.

This only applies to formal presentations and public comments.  Publicly commenting on private conversations is absolutely out as far as I’m concerned, and I will only write about side conversations the person I’m talking to knows my intentions beforehand.

Invitation-only meetings: Definitely no live tweeting, and no blogging unless express permission is given.

Meetings with clearly stated reporting limitations: Generally, no live tweeting, and abiding by the rules when it comes to blogging.

Expert presentation & discussion of non-peer reviewed data. If the aim of the meeting is to seriously assess and discuss someone’s unpublished research, I would hesitate to live tweet.  I might blog – but only if it seemed appropriate given the state and significance of the research.

Open conferences (i.e. anyone who pays can attend) where researchers are reviewing the state of knowledge, presenting published data, or clearly think they are the bees knees and everyone should know it. These I see as fair game for live tweeting and blogging – without the permission of the speaker.

Public meetings, where anyone can attend and there is no entrance fee. Open season as far as tweeting and blogging go.

I will probably modify these with time and experience – it’s a first stab after all.  But I think it’s a necessary one.  Widespread communication through social media is a reality, it is challenging how things are done, and a new equilibrium needs to be found between those providing information and those using and distributing it.  The danger is that without some honest soul-searching by everyone involved, the new equilibrium could be more detrimental than beneficial.

And on a final note, Daniel MacArthur wrote a very gracious yet insightful response to Genomeweb’s concerns – evidence (if you needed it) that serious commentations are committed to getting this right, for everyone’s benefit.

This is by way of a quick follow-on to yesterday’s post on the number of people on Twitter  following science-focused users.  As was pointed out, just logging the number of followers someone has on twitter is a poor indicator of either success or influence.  So, spurred into action, here is a rather more sophisticated analysis of the “influence” of the tweeps in David Bradley’s list of “Scientific Twitter Friends:”

This is not the clearest graphic – even if you click on it to open a larger version – so you might like to play around with the the original.  A limited interactive version showing social capital second order followers is also included below. As in the previous post, they are based on data visualization routines on the Many Eyes website…

Earlier today, David Bradley over at ScienceBase announced that his growing list of “Scientific Twitter Friends” has hit the 400 mark.  Given the recent explosion in Twitter use, I was intrigued to see how these science-types are faring in the brave new world of on-line communication, 140 characters at a time.

This is a bubble chart of David’s science “tweeps,” courtesy of the Many Eyes website (click on the image to play with the original, or see the interactive version below) – the area of each bubble represents the number of users followers for a particular tweep…

It’s not a particularly sophisticated analysis – number of followers is a very crude measure of success or impact on Twitter.  But it does give an indication of where Twitter users with a science-bent stand.  as you would expect, there are plenty of tweeps with modest followings – the mean number of followers is 528 from this particular analysis.  That is a drop in the ocean compared to some of the celebrity power-users now populating Twitter.  But it does represent a respectable foundation for a science-based social network.  And as can be seen, there are a a number of users here who have followers in the four and five digits.

One of the reasons for carrying out this exercise – apart from looking for any excuse to do some real work – was to get a feel for how science information is beginning to flow between different communities and users on the web.  This is just one data-point – a lot more work is needed before the importance of social media to science communication becomes clearer.  But it does at least suggest that scientists and science writers are beginning to embrace new social media.

This can only be good news for science – it might actually mean that people generating and using information begin talking to one another at long last!

Notes:

For this analysis, I knocked out any users with no followers, and two tweeps with excessively high followings (@guardiantech and @Astronautics) – so they didn’t unduly bias the assessment.

And here’s the interactive version of the bubble plot:

13 “Twits” Who Will Change Your Perspective on Reality

Back in the days when Twitter was a mere slip of a social media service—around four months ago by my reckoning—it was a byword for meaningless web-chatter and banal exchanges.  But the service is growing up rapidly —not only in the number of users (which is skyrocketing, especially amongst the middle-aged apparently), but also in the quality and relevance of “tweets” posted by users.

There are a growing number of people on Twitter who genuinely challenge and engage others—in science and technology, as much as in other areas.  These “tweeps” (or “twits” as my wife prefers—which I hope is no reflection on my own “twittering”) are helping mesh together a web people from all walks who are more interested in discussing the latest science and technology—and its implications—than what Britney Spears had for breakfast.

Over at mashable.com, I’ve just posted a list of “13 “Twits” Who Will Change Your Perspective on Reality.” If you are still trying to work out what on earth Twitter’s about, or are looking for some stimulating science and technology-related company in the “Twitterverse,” check these “twits” out.

It’s an eclectic list and includes somebody who’s been dead and buried a good few years, and someone else who doesn’t post on science and technology tweets, but whom I enjoy reading anyway!  The common thread though is that they all post stuff that makes you think—even the dead guy. (Especially the dead guy, actually).

Of course, the list is hopelessly incomplete.  So please feel free to add anyone that should have been there but isn’t—either in the comments here, or over on Mashable.

And happy tweeting!

EndNotes

Sadly, I became an avid “twit” after the rather naive Emerging science and technology at 700 characters per day experiment back in December.  I can now be found adding my banalities into the mix of relative profundities on Twitter as @2020science.  Or if you prefer, you can read them in the sidebar of this blog!

My thanks to Ruth Seeley for being such an honest and proficient editor on the Mashable blog, and to Lon S. Cohen who gave me the idea in the first place – although he probably didn’t realize it at the time!  They can both be found on Twitter as @ruthseeley and @obilon

Part 3 of a series on rethinking science and technology for the 21st century

I’m fascinated by the power of communication.  The idea that someone’s perceptions and actions can be changed by information received through sight, sound or touch, is rather profound.  Even more so is the idea that, through exchanging information and ideas, people can influence and change the course of whole societies.

Communication—my third “C” in this series on rethinking science and technology for the 21st century—is powerful.  It always has been.  But rapid changes in how we communicate with each other are rewriting the rules on how that power is manifest.  And no-where are these changes as significant as in the development and use of new science and technology.

I’m not going to write extensively about how modern communications are changing the world here—there are a thousand and one commentators discussing the emergence of the Flat Earth, globalization, Web X.0 and other ramifications of living in an increasingly connected world.  But I do want to establish how communication is a critical factor influencing the future development and use of science and technology. Because when combined with the other two “C’s”—Coupling and Control—new challenges arise that are going to be tough to handle from a 20th century perspective.

In broad terms, the changing face of global communications is affecting science and technology in three ways:

First, advances in modern communication are revolutionizing “peer-peer” and “peer-lay” information exchange. Twenty years ago, rooting out scientific information was a physical adventure.  I remember cycling between libraries, chasing up reference trails, lugging weighty tomes around while wandering along seemingly endless shelves of books.  I could get quite nostalgic about time spent surrounded by piles of journals in musty Cambridge libraries.  Nowadays of course nothing is further than the click of a mouse away.  And it’s not just journals—the internet is flooded with a wealth of information which is richer than could ever be imagined 20 years ago.  Researchers have access to vast arrays of new information in their own field, as well as new findings in other disciplines.  The result is a cross-fertilization that is driving the generation of new scientific knowledge and technology innovation at an unprecedented rate.

But the same information is also available to non-experts—the “lay public.”  Now, anyone can in principle access in-depth information on the latest scientific breakthroughs.  And where they might struggle with esoteric science, there are a growing number of resources that translate and repackage the knowledge into more manageable chunks.  As a consequence, science and technology are being democratized.

It’s still a relatively select community that is benefiting from this increasing access to information.  But the day is quite possibly coming when the current intellectual hierarchies will begin to crumble, and a new science and technology order will emerge.

Secondly, advances in modern communication are revolutionizing the exchange of ideas. Ideas propagate along lines of communication and change individuals and groups who come into contact with them.  In the past, geographical and technological barriers have limited the growth and influence of ideas around the world.  But with the advent of Web 2.0 and whatever comes next, traditional barriers are being blown away.  And as a result, new ideas are spreading and potentially changing how people think and behave faster and more unpredictably than ever before.

This new interconnectedness will have profound implications on global society.  And this will include a clear impact on science and technology—one that we are already seeing.  Through advances in global communication, individuals and groups will form opinions and ideas on emerging science and technology as new knowledge and abilities are developed.  In effect, the old intellectual command and control model is disappearing.  Which means that the debate over how science is done, what areas of science are pursued, and which new technologies are developed (and how) is now very public, and very global.  And there is no guarantee that the participants will have the same understanding of or respect for hard data as the people generating them.

This global exchange of ideas leads into the third way in which advances in communication will affect science and technology: Decentralization. Advancing communication is empowering citizens to influence the course of science and technology in ways that transcend traditional boundaries.  If a group of people decide they don’t like a new technology, it’s relatively easy for them to mobilize and hinder the progress of that technology.  It happened with genetically modified organisms, and there have been concerns that it could happen in other areas like nanotechnology or synthetic biology (for example).  And with this increasing decentralized influence, scientists can scream and shout until they are blue in the face about the authority of hard data—if people don’t want something, it ain’t going to happen.

Which means that if science and technology are to be used wisely and beneficially over the next century, this new communication landscape needs to be understood and navigated.

In the original lecture on which this series is based, I used two examples to illustrate the implications of rapidly evolving global communication—one rather trivial, the other slightly less so.

First, I wanted to illustrate the rapidity with which communication networks are growing around the world, and how information and ideas propagate along these.  I chose Twitter, and one particular user; the British comedian and raconteur Stephen Fry—this is the trivial example.

The growth of interest in Twitter has been phenomenal, and only matched by the growth in stature of users like Stephen Fry (or to use his Twitter persona, @stephenfry).  For the uninitiated, Twitter builds on text messaging by allowing users to send messages of 140 characters or less to other users.  Any message you post can be read by anyone else, although it is delivered directly to your “followers.”  And likewise, any message posted by someone you “follow” is delivered directly to you.  You can then (if you so choose) decide to redirect—or “ReTweet”—that message to your own followers.

In this way a complex web of rapid global communication is established.

Four weeks ago when I was preparing to speak in Oxford, @stephenfry had the fifth highest following on Twitter—with around 280,000 followers.  It’s a testament to the growth of the medium that now—just four weeks later—he is 22nd in the popularity stakes (with 380,000 followers).  But the ranking is not important.  Think, for a moment, of the reach @stephenfry has if he comes up with a bright idea and posts it on Twitter.  380,000 people will receive and (hopefully) read this new nugget of information.  Some of them will pass it on—especially if it’s a good one.  And some of these will pass it on in turn, perhaps embellishing the idea.  The result is a web of nodes and connections that favor the propagation and evolution of ideas over a potentially vast number of people.

The top-subscribed Twitter user is currently @cnnbrk (breaking news from CNN) with 820,000 followers—more than the circulation of a small newspaper and climbing by over 12,000 followers a day.  Just imagine the reach of ideas propagated through this network, especially as they get picked up and pass on by other power users.

Twitter is just one example of how people are interacting through the web and information and ideas are propagating in ways that are completely alien to how the world worked a few years ago.  But there’s another side to this.  A flood of information with inadequate filtering and interpretation is simply noise, and becomes more ineffective the more of it there is.  For the communication revolution to go anywhere, there need to be new ways of handing the mass of information we are exposed to.

Not surprisingly, this is happening.  The second example here is just one of many where new innovations are helping to assimilate this flood of data.  It comes from Pranav Mistry in Patti Maes’ group at the MIT Media Lab, and is part of the Sixth Sense project:

[For a fuller explanation of what you are seeing, check out Patti Maes’ TED video]

What you see is an attempt to contextualize the mass of data available over the web, by using complex information collection, processing, retrieval and presentation.  The system comprises a video camera, projector and web-enabled phone, worn by the user.  By integrating all three components, the wearer can now interact with the web in a very intuitive and context-specific manner—almost as if there was an additional sense reaching out into cyber space.

Using interactive systems like this—which I guarantee are going to become very sophisticated very fast—the door is opened to exchanging information, ideas and influence between real and virtual communities around the globe in ways which will have a profound impact on how we live our lives.  This combination of information and interactive processing is perhaps what makes this “C” such a powerful agent for change when it comes to science and technology.  But powerful as it is, the influence of communication is enhanced significantly by the third “C”—Control.

Over the next few posts, I’ll be exploring this idea of control in more depth.

Notes

Rethinking science and technology for the 21st century is a series of blogs drawing on a recent lecture given at the James Martin School in Oxford.  This is a bit of an experiment—the serialization of a lecture, and a prelude to a more formal academic paper.  But hopefully it will be both interesting and useful.  I’ll be posting a “rethinking science and technology” blog every week or so, interspersed with the usual eclectic mix of stuff you’ve come to expect from 2020science.

Previously: Coupling: Actions and consequences in a shrinking world

Next: Control: Gaining mastery over the world at the finest level

[Updated 4/8/09 - slide of MIT Sixth Sense system added]

Getting serious with Twitter

I’m gutted.  I thought that blogging was where it is at—the cutting edge of the “new media” wave transforming modern communication.  But I now discover that I’m at least four years behind the times—a veritable dinosaur in the world of “Web 2.0!”

Which is why I’m pushing myself out on a limb with a bold experiment in social network communication this week!

November’s edition of Wired Magazine ran a story entitled “Twitter, Flickr, Facebook Make Blogs Look So 2004.” And just in case you didn’t get the message about blogging from the title, the opening paragraph rammed it home:

“Thinking about launching your own blog? Here’s some friendly advice: Don’t. And if you’ve already got one, pull the plug.”

The blogosphere is being deluged by a stream of “paid bilge” according to the article… drowning out the voices of original writers.  But as one form of self-expression becomes overwhelmed, others emerge—and social networking sites like YouTube, Flickr and Facebook are where the action is these days.

Add to that list Twitter—a high profile “microblogging” site that is attracting a growing following.  According to Wired,

“Twitter … is to 2008 what the blogosphere was to 2004.”

However, Twitter limits posts to text messages no longer than 140 characters—including spaces.  Great for letting friends and family know you have just had your first coffee of the day.  But what if you want to impart some slightly more substantive words of wisdom?

I suspect that web-based social networking is in danger of flooding our lives with trivia, making it increasingly hard to assimilate and make use of complex information.  Yet if this is where people are exchanging ideas and “hanging out” these days, perhaps it’s time to experiment with using the “new” new media, rather than simply dismissing it.

And so for the next five days—starting Monday—I propose to roll up my sleeves and attempt some serious “twittering.”

Here’s the plan:  Between Monday December 8 and Friday December 12, I aim to submit five non-trivial posts a day to the 2020science Twitter feed that tackle emerging science and technology issues—that’s emerging science and technology at 700 characters per day!

You can follow my progress at http://twitter.com/2020science.  You can even sign up with Twitter and comment directly on the posts—as long as you keep within 140 characters!

I suspect I’m setting myself up for failure here.  But I did want to see whether it’s possible to convey something meaningful within the attention-span of today’s web-users.  Because—and this is probably important—as more and more people become part of the digital sound-bite community, effective communication will depend on working within the new media—despite its flaws.

Happy Twittering!

(Expressed in 2720 characters – including spaces)