For the second year in a row, I live Tweeted and Visualized the Internet Strategy Forum Summit at the Governor Hotel in Portland, OR.

My goal was to track Twitter volume, speaker quotes, and general buzz around the event of every attending Twitterer in the audience. I had to formalize the data and take samples during many parts of the day to get a solid visual.

Instead of digging through pages of Twitter data with the search term #ISF09, the method here allows the audience as well as speakers to see how their speech ranked in comparison others at the conference. This way, one can see exactly the topics that hit the audience the hardest.

I used a Java Applet called StreamGraphs to visually track the Internet Strategy Forum Summit. The app was built by Jeff Clark. You can follow him @JeffClark on Twitter.

Standardizing the Data

StreamGraphs has some limitations. It only shows the last 1,000 tweets and thus it must be queried in real-time, during an event, to get usable results. The first thing to do was to standardize the hashtag. Some Twitter users were Tweeting with @summit, #isfsummit09, or #isf09. For the best data to be presented, users had to Tweet using one hashtag. I did a Twitter search for everyone following @summit OR #isfsummit09 OR #isf09 OR the Governor Hotel and began following them. Then I @’d them, welcoming them to the Internet Strategy Forum Summit and added an #isf09 hashtag to the end of each Tweet. I watched for people questioning as to which hashtag to use and informed them that #isf09 was shorter and better.

By 10:47, I had regular data and was able to begin tracking the Internet Strategy Forum Summit. Katherine Durham’s Tweets were not able to be recorded into the graph, but Shelia Tolle and the speakers after her were picked up. This was due to a limitation of the StreamGraph Java Applet (StreamGraph only shows the last 1,000 Tweets). So alas, we missed Durham’s excellent words: “Flat is the new up“.

And the second sample was taken from 10:08 to 2:37. The second sample did a better job at gathering the overall sentiment and buzz of the conference. It is evident from the image that Jeremiah Owyang was the speaker that captured the audience’s attention the most.

What Was Shown:

The interesting part about visualizing data in this way is that it shows that there is an inherent difference between what a speaker says and what they audience values. The conversations bursts worked just like sine waves as audience began to engage with the material of each new speaker. As memorable quotes were released into the audience, a lot of tweeting and retweeting coverage occured, melding some of the terms into like-groups. The graph shows that people tweeted about the speaker during the middle of the speech as opposed to at the beginning or end of the speech.

The First Burst: Shelia Tolle

Vice President of Marketing, Intuit Small Business Group. TOPIC: Combining eCommerce and Community: It’s a New Normal…and, There’s
No Going Back

The three words most associated with Shelia’s speech were online, Twitter, and Social.

BenZee: Fastest growing group on Twitter and facebook is people over 40.

CommunityMGR: Fastest growing group on Social Networks (ie: Facebook) are over the age of 45! Social Equillibrium from young to older. #ISF09

CommunityMGR: Channels like Twitter allow companies to help customers WHERE THEY ARE. Personalize with indiv photos, NOT logos as avatars. #Intuit #ISF09

TMMPDX: Intuit helping customers where they are - Twitter. @intuit draws the ire from professional haters online - Sheila Tolle. #isf09 #isfsummit09

cyndibrigham: Help customers where they are. This is the work I focus on through online syndication. Go to where the people shop and research #isf09

tmmBosley: turn bullhorn around, be part of the community, live your higher purpose, create amazing, embrace chaos! #isf09 Sheila Tolle

The Second Burst: Lisa Welchman

Here we can see the major takeaways from @lwelchman’s speech on change.

Top tweets: “orgs need to handle change internally. All communications need to change, and people don’t want to grasp impact, says @tom_bennett and @tmmBosley.

@smdempsey: @CommunityMGR Game has changed, but the internet was just the impetus. Time to rethink the model; biz as usual is not sustainable.

@blocheads: Effecting change is hard. I’ve asked clients to agree to a “We promise to do whatever you say clause, but no takers yet.
@tmmBosley: What to do? Systematic change: Figure out guiding principles in your organization (like Intel has done right @bryanrhoads?

Key Point: Chief Content Officer

At 11:11, @lwelchman brought up the idea of the Chief Content Officer, or the Chief Web Officer.

rahelab: Time has come for a Chief Content Office, Chief Web Officer, ect as these areas have become critical to web ops.
close2open: “Why can’t there be a Chief Content officer?
tmmSabrina: Lisa from @welchman Start a management REVOLUTION! Chief Content Officer, Chief Web Officer, ect. Amen Sister!

But I was told later that it was not about hiring a Chief Content Officer, but about becoming one.

Retweets of this comment appeared again at 11:49.

10:40: We all have a ‘wierd background’ - I’m a philosophy major w/Phorics minor and did did vocal opera. what does that make me? a Web person.

Caseorganic: RT @jeffreybunch: @lwelchman inspiring the oppressed web masses at #isf09!

imeldak: The CIO should be responsible for driving content, web and technology revolutions in the C Suite

@lwelchman was an excellent speaker.

The Third Burst: Jeremiah Owyang

The audience took away major points from Jeremiah Owyang’s speech, including ideas related to the web, context, users, eras and years, pages, and community. The social theme resonated most with the audience, as well as being a major theme of the conference.

The idea of eras was a new and interesting take on the standard ideas of business the and social web. One of the main takeaways concerned the fact that a company could actually have a 5 year media plan instead of a year to year thing. He outlined the social eras to come so that businesses might plan instead of being left behind.

Era

CommunityMGR: 5 eras of social web: Relationships, Functionality, Colonization, Context & Commerce.

Web

Webtom_bennett: Allow users to surf the web within your experience (put your wrapper on it).

msdouglass: Social web colonization is coming to your business. Will you be France? Belgium? Ivory Coast? USA? Offline lessons abound.

Context

jdenizac: People will surf in social contexts, even if your site is not social. eg, digg bar.

tom_bennett: Social Context - contextualized experience based on universal IDs is coming.

Page

agray: Registration pages are going away - the way you collect leads online with change.
@thisKat: @agray More details! Live Tweet this! So many marketers are slaves to the registration page.
NathanJWagner: Registration pages will change…lead gen and CRM reporting will change…SM sites will get more traffic than corp sites.
Caseorganic: Registration Pages Going Away. May be able to measure by # of fans, engagement you have instead of signups.

Community

Tom_bennett: Agencies will appear that represent communities, not brands.
tom_bennett: Functionality - shatter your corporate website and let it spread within the community.
CommunityMGR: Social Networks will become next generation CRM Systems. Ad agencies may flip to representing the Community.

User

caseorganic: Social networks becoming operating systems - can put apps on top like Scrabulous and interact with users where they are.
Rahelab: Social functionality: more like operating systems. Apps on top of platforms-Facebook, LinkedIn apps. “Go where users are.” Not mature yet.
BenZee: On the web: technologies evolve, users adopt then companies adapt.

Johan’s speech about Intel Corp’s Keynote spurred a lot of Tweets about Intel, and thus the Intel name is associated with it. Most of the Tweeting was done towards the first of part of Johan’s speech, as well as the discusion of a very nice Intel ad about the co-founder of the USB. Towards the end of the speech, and the subsequent panel, the electronics in the room ran out of batteries, making it impossible to cover the event via Twitter. I was told that iPhones and Blackberries were also running out of power. Although some battery life may have been restored during lunch, the life quickly ran out. I saw many audience members turn towards pen and paper to take notes for the rest of the conference.

Conclusion:

There are many graphs like this available online. Most are made by students at colleges, and a lot have to do with graphically displaying content volumes. I found this analytics visualizer to be exceptionally powerful because of its ability to track word volume over time.

The applications for this type of visual presentation of information are vast. During the ISF after party, I determined that these graphs would be an invaluable tool for examining PR statistics over time. If I sat down and pulled apart the code with someone, it would be fun to develop this graphing system into an extremely granular tool for online reputation management.

Data Dimensions:

My research depends on attending conferences because my current focus is on visualizing data with 4 main dimensions.

1. Time
2. Volume
3. Keyword
4. Event/Person

In this way, data becomes more like an audio file, and even closely resembles it. It is a friendlier way of viewing trends, and is more accurate (because of the added dimension of volume) than

Tool Limitations:

Currently, the tool I am using is Java based. It does not yet allow the user to set periods of time, and does not have the server capabilities to store server data. It is a brilliant data analytics tool, and if it were to allow a greater amount of granularity (in terms of keywords), as well as time range, it would prove to be an invaluable tool for tracking Public Relations. Currently, it is possible to do this, it just takes a longer amount of time to do so.

I approached Jeff Clark, the tool’s developer, about collaborating with him to create a more robust version that would incorporate a larger time frame, clickable data formats (I have a paper prototype of all of this), and a zoom feature. He declined, so the tool will stay where it is. If he releases a new version, I will be the first to use it.

There are so many great potentialities with a tool like this, because being able to visualize data over time with an extra dimension of volume is really exciting. Please let me know if you’d like to work on an open source version of it with me.

Now What?

Systems are optimal when the amount of time and space it takes to get pieces of relevant data from one person to another continues to decrease. Those designs/processes that exemplify this paradigm will be successful in the future economy. Systems like these that track the most important data points will be an important part of your complete data breakfast.

About:

Amber Case is a cyborg anthropologist, internet marketer, and speaker from Portland, Oregon. You can contact her at caseorganic at gmail.com, or on Twitter at @caseorganic.

Many thanks to Steve Gehlen for running the Internet Strategy Forum Summit and inviting me back to the conference to visualize the data streams.

 

 Hazelnut Tech Talk Episode 11 [23:46m]: Play Now | Play in Popup | Download (423)

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Hazelnut Tech Talk is a collaboration between Amber Case and Bram Pitoyo

This episode features Troy Harlan, wherein we talked about information gathering, filtering and consuming (naturally,) human factors, trilobites, reading at 2,000 words per minute, INTP’s, striving for objectivity, The Black Swan, hunches, and why it’s better to “have no map at all than have the wrong map”—all recorded on the road from St. Johns to downtown Portland.

Today I live Tweeted the Internet Strategy Forum at the Governor Hotel in Portland, OR.

A few days ago, @infovore of Twitter sent me the link to NeoFormix, an experimental Twitter processor. I was really happy about this, because I love infographics, and I love to mess around with new types of data presentation. The NeoFormixTwitter StreamGraph was built by Jeff Clark, a brilliant developer. You can follow him @JeffClark on Twitter.

My goal was to track Twitter volume, speaker quotes, and general buzz around the event of every attending Twitterer in the audience. I did not want to have a sheet of messy or relatively non-granular data like Summize or Tweetvolume provide. I wanted to show volume over time, and for this I determined that graphic output was needed.

There were two hurdles I had to bypass before being able to adequately gather uniform data. The first was that the tracking hashtag for the ISF was not stable. Tweets of attending members migrated from @summit to #ISF08 to #ISF, and thus data that coverage was spottier than necessary.

In order to solve this problem, I began to gather every Twitter user that was attending the ISF into a text document. Then I sent out Tweets welcoming them to the conference. At the end of each welcome Tweet, I signed it @summit #ISF. As I welcomed more Twitterers and gained more followers, I dropped the @summit and Tweeted as much as possible about the event with others, using simply #ISF to sign my post.

By around 10:30 Am, the #ISF hashtag was well on its way. Once this hashtag standard came about in a uniform manner, I was able to run much more accurate analytics on the data. I was then able to use the word ‘ISF‘ to track top word volumes related to most of the Tweets concerning the Internet Stragety Forum.

What It Shows:

The period of time that the graph shows begins during the middle of Geoffrey Ramsey, Co-founder & CEO, eMarketer’s speech, covers the speech of Dan Stickel (CEO, WebTrends) speech and ends a little before the end of Nancy Bhagat Vice President, Sales and Marketing Group; Director, Integrated Marketing, Intel Corp’s speech.

What Was Shown:

The conversations bursts worked just like sine waves as audience began to engage with the material of each new speaker. As memorable quotes were released into the audience, a lot of tweeting and retweeting coverage occured, melding some of the terms into like-groups. The graph shows that people tweeted about the speaker during the middle of the speech as opposed to at the beginning or end of the speech.

The First Burst:

In the first Twitter lump, Geoffery Ramsey talked about ‘FOG’, or the Fear of Google. You can track it in this graph! Fear shows up, as well as Google. During this time, attendees were using @summit more often than #ISF to track the conference, which shows.

I am trying to determine why “life” showed itself so often, but “social, network, online, trust, marketing and show” made a lot of sense.

The Second Burst:

Presenter Dan Stickel was not as quotable, but the Twitter reporters recorded his name, and the fact that he was speaking. At first they used both his first and last name to ID him, and then used his last name, for the sake of brevity.

The other lumps show that there were tweets during this time, some attributed to his name, but none that were unified. I.E., many Twitterers did not quote the same parts of his speech at the same time, or in enough volume in order to show up on the graph as an actual word.

The Third Burst:

Nancy Bhagat of Intel Corp’s Keynote spurred a lot of Tweets about Intel, and thus her name is associated with it.

There was also @summit, presentation, marketing, great, Nancy, and bhagat. Most of the Tweeting was done towards the first of her speech, as well as the discusion of her status as an Intel worker.

Conclusion:

There are many graphs like this available online. Most are made by students at colleges, and a lot have to do with graphically displaying content volumes. I found this analytics visualizer to be exceptionally powerful because of its ability to track word volume over time.

The applications for this type of visual presentation of information are vast. During the ISF after party, I determined that these graphs would be an invaluable tool for examining PR statistics over time, or, as I discussed with Dan Gaul, Kent Lewis and Geoffrey Ramsey, the highlights of one’s speech. If I sat down and pulled apart the code with someone, it would be fun to develop this graphing system into an extremely granular tool for online reputation management.

After the conference, Kent Lewis of Anvil Media suggested that I demonstrate the report to Geoffrey Ramsey, because the graphics allowed a quick and easy way to show him the highlights of the speech he gave. When I showed him, he was really excited about the results, because he did not know how to gauge the success or failure of his speech.

Instead of digging through pages of Twitter data, even through Summize.com (with the search term #ISF), the method I developed allowed him to see just his speech, and exactly the topics that hit the audience the hardest.

Data Dimensions:

My research depends on attending conferences because my current focus is on visualizing data with 4 main dimensions.

1. Time
2. Volume
3. Keyword
4. Event/Person

In this way, data becomes more like an audio file, and even closely resembles it. It is a friendlier way of viewing trends, and is more accurate (because of the added dimension of volume) than

Tool Limitations:

Currently, the tool I am using is Java based. It does not yet allow the user to set periods of time, and does not have the server capabilities to store server data. It is a brilliant data analytics tool, and if it were to allow a greater amount of granularity (in terms of keywords), as well as time range, it would prove to be an invaluable tool for tracking Public Relations. Currently, it is possible to do this, it just takes a longer amount of time to do so.

My goal is to approach the tools’ inventor, Jeff Clark, about collaborating with him to create a more robust version that would incorporate a larger time frame, clickable data formats (I have a paper prototype of all of this), and a zoom feature. A sort of map of time, or an audio burst.

The interesting part about visualizing data in this way is that it shows that there is an inherent difference between what a speaker says and the audience “hears”. Hearing, in this case, is defined by how the speaker’s name, company, and words are picked up by microbloggers and re-tweeted online.

Future Considerations:

If tech conference attendees were prompted to provide their Twitter id with their conference registration, tracking processes could be preformed more easily (this was the case at Gnomedex, a conference I was invited by Chris Pirillo to attend).

More Projects:

This project is just one of the experiments I’m working on. As it is most easily done during conferences, I have to wait for conferences with a substantial amount of Twitter users.

I’d like to be able to show this in real life, because its more enjoyable to get really excited about the data. There are so many great potentialities with a tool like this, because being able to visualize data over time with an extra dimension of volume is really exciting.

It’s also great to be able to discuss new methodologies with people because so many more conclusions can be gleaned from discussion. I recently presented this technique to a group of Portland tech people at a sort of software demo session. There was a lot of great feedback there, and new ideas gleaned from it. It’s amazing, the value and speed of digital communities.

In Essence:

I’ll be applying this tool to the crowd and will be trying to trick it out, or hack it to be able to show more statistics over time. I’ll be doing the standard audio recordings of the entire conference, so that I can compare and contrast what was Tweeted vs. what was said in real life. I’ll probably be taking about 50 graph samples, so that the relative volume and interest in each speaker can be tracked. There will be a lot of write-ups about the uses of this type of visualization, and how it can be applied to PR campaigns.

Now What?

Systems are optimal when the amount of time and space it takes to get pieces of relevant data from one person to another continues to decrease. Those designs/processes that exemplify this paradigm will be successful in the future economy.

About:

Amber Case is a cyborg anthropologist, internet marketer, and speaker from Portland, Oregon. You can contact her at caseorganic at gmail.com, or on Twitter at @caseorganic