Go See Your LinkedIn Social Graph - Visualization Tool

[caption id="attachment_1082" align="aligncenter" width="550" caption="Click to Enlarge"][/caption] Today, I stumbled upon a really cool social network graphing tool from the creative folks over at LinkedIn (part of the LinkedIn labs projects).

Basically, once you connect your account with this LinkedIn web application, you'll see a visual rendering of your LinkedIn network, neatly organized by colorful groups of your network connections you've created over time.

So, for example, my connections relating to my 10 years in New York and my Social Media Club group in Rochester, NY are grouped together. Not only are physical connections like these obvious, but also virtual connections, such as "social media" connections. My largest network is comprised of my Technology industry connections; no surprise there as technology permeates my entire career.

[caption id="attachment_1083" align="aligncenter" width="550" caption="Click to Enlarge"][/caption]

To get started go here: http://inmaps.linkedinlabs.com/network and allow LinkedIn labs to connect with your profile.

When complete, you can view the social graph rendered and then "label"your networks.

TIP: Use the magnifier tool in to zoom in and read the names in each color area. Then begin labeling accordingly.

I find this sort of visual rendering to be very appealing, not only because I am a visual learner, but because it allows one to see how their career connections are related. You can also easily spot key influencials and people who are very connected to the same circles of friends and industry connections you have. Some of those folks are the same ones who helped me make connections... very interesting data!!

What do you think of this? Do you find this useful and intriguing like I do? Does this kind of tool make it easier or harder to group your network of friends and professional connections?

Here's a visual step-by-step of the screens you'll see as  you generate your very own LinkedIn network social graph:


Twitter's new RT Feature: What it means for News Industry and Influencers

As I am sure you've all seen the fairly new "retweet" (RT) feature released by Twitter, it has not been fully understood to date.  Influence on twitter was previously quite easy to track, but now with the new RT feature, it's becoming less clear who's influencing who.  For example, prior to the new RT feature a user would "RT" a tweet by simply copy/pasting the content like so: "RT @username: original content" (sometimes a comment was added too).  Then, the RT would be published out to the RTer's followers.  Some of those followers would then RT the RT, thus establishing a clear line of influence, stemming from the originating tweet and RTs (to a point, of course).

What the old RT model showed was a path of influence on twitter (and how information travels - interesting stuff for sure!).  Now comes the new RT feature and this "influence" model is completely disrupted.  No longer can we track who's RT'ing what.  It's been completely flattened out. So, folks who RT can no longer see who is RTing a post after them.  So we lose the whole influencer in the middle (middle man influencers).  Now it's all flat - just the original post and a lateral line to the RTs.  Whereas, previously we had the original post and a plethora of tangential RTs, with some fairly obvious track-backs, so to speak.

Why would twitter do this?  Two good reasons are potentially driving this decision.  First, data management and data storage optimization.  Second, establishment of twitter as an authentic news source (more on this in a bit).

Data management is a tricky proposition when a web startup takes off and begins to manage millions of records in their database(s).  The new RT feature is a smarter implementation at the database level.  Now with the new RT feature, the database could store just 1 original tweet plus a bunch of variable flags turned on/off (1 or 0) for the RT usernames versus the old RT model of originating tweet plus copies (e.g. 72 copies of that same tweet +/- variations thereof).  Thus, this is a very smart approach to shrinking the data footprint of RT content.

The whole "News industry" is currently undergoing a rapid change much akin to the industrial revolution.  Companies and jobs are folding every day as the old model of journalism is eclipsed by the new real-time web and emergent citizen-journalism model.  Twitter is a major component of this new version of "news."  Thus, it is in twitter's best interest to develop a trusted system for delivery of real-time news that is timely, reliable, authentic and trackable.  Since, the new RT feature preserves the originating author's name and content, this perfectly fits with the news model.  Now we can see who tweeted what without alteration.  That is a huge move towards authenticity on the web - a must for reliable and trusted news content.  Twitter is positioning itself to be the most trusted news source on the web and this new RT feature goes a long way to provide just that.

Originators of news on the web will feel this impact in a number of ways.  Specifically, if they are RT'ed, then their tweets will show "Retweeted by x and x others " (shows amount of RTs by users - think "reach" on the web).  For what I call the "middle man" influencers - the RTers out there - they will feel a negative impact as they no longer are associated with the originating content (and downstream RTs) as in times past.  Now, when a user sees a RT it just shows a pile of #s, so the middle man no longer benefits, i.e. their name is not associated with the originating post as it used to be (middle man influencers will see a drop in engagement levels based on RTs).

Overall, I think this is a fabulous move by twitter and applaude them for making the switch.  It's smart and disruptive.  I like it.  It shows twitter has smart folks at the helm who understand the web and the future of it very well.

For me, I will definitely  use the new RT feature anytime I want to preserve the original tweet author/content.  If I need to add something (and there's char space!) then I will add my 2 cents and RT that.  What's your take? Do you like or dislike the new RT feature?  Think of other reasons why twitter would implement this new RT feature and let me know what you see.  I'd love to hear all your feedback and ideas on this!

The Average Facebook User Views 662 Facebook Pages Per Month [chart] /via @alleyinsider

The average Facebook visitor views 661.8 pages on the social network each month, reports Website monitoring service Royal Pingdom (citing Google AdCounter). Facebook blows away the competition when it comes to this single engagement statistic.

Visitors to Facebook's nearest rival, Hi5, only view an average of 351.2 pages per month. MySpace comes in at 261.8 monthly page views per visitor.

Point is: Not only does Facebook have a huge user-base -- about 350 million people check the site at least once a month -- it has a very engaged user-base. No wonder Facebook ads are finally gaining traction.

fb chart page views daily

November Sees Number of U.S. Videos Viewed Online Surpass 30 Billion for First Time on Record

November Sees Number of U.S. Videos Viewed Online Surpass 30 Billion for First Time on Record Hulu Extends All-Time High to 924 Million Videos Viewed

RESTON, VA, January 5, 2010 – comScore, Inc. (NASDAQ: SCOR), a leader in measuring the digital world, today released November 2009 data from the comScore Video Metrix service, showing that more than 170 million U.S. Internet users watched online video during the month. Online video viewing continued to reach record levels in November with nearly 31 billion videos viewed during the month, and Google Sites accounting for 39 percent of all videos viewed online in the U.S.

Top 10 Video Content Properties by Videos Viewed

Google Sites continued to rank as the top U.S. video property in November as it delivered 12.2 billion videos viewed with YouTube.com accounting for nearly 99 percent of all videos viewed at the property. Hulu ranked second with 924 million videos viewed (3.0 percent) followed by Viacom Digital with 500 million (1.6 percent) and Microsoft Sites with 480 million (1.5 percent).

Top U.S. Online Video Content Properties* by Videos Viewed

November 2009

Total U.S. – Home/Work/University Locations

Source: comScore Video Metrix

Property Videos (000) Share (%) of Video

Total Internet : Total Audience 30,986,670 100.0%

Google Sites 12,215,994 39.4%

Hulu 923,805 3.0%

Viacom Digital 499,497 1.6%

Microsoft Sites 479,638 1.5%

Yahoo! Sites 470,804 1.5%

Fox Interactive Media 446,460 1.4%

Turner Network 336,952 1.1%

CBS Interactive 287,588 0.9%

AOL LLC 227,797 0.7%

MEGAVIDEO.COM 201,199 0.6%

*Rankings based on video content sites; excludes video server networks. Online video includes both streaming and progressive download video.

Top 10 Video Content Properties by Viewers

More than 170 million viewers watched an average of 182 videos per viewer during the month of November. Google Sites attracted 129 million unique viewers during the month (94.7 videos per viewer), followed by Yahoo! Sites with more than 55 million viewers (8.5 videos per viewer) and Fox Interactive Media with 50 million viewers (8.9 videos per viewer). The average Hulu viewer watched 21.1 videos during the month, representing another all-time high for the property.

Top U.S. Online Video Content Properties* by Unique Viewers

November 2009

Total U.S. – Home/Work/University Locations

Source: comScore Video Metrix

Property Unique Viewers (000) Average Videos per Viewer

Total Internet : Total Audience 170,647 181.6

Google Sites 129,037 94.7

Yahoo! Sites 55,145 8.5

Fox Interactive Media 49,981 8.9

CBS Interactive 47,460 6.1

Hulu 43,738 21.1

Microsoft Sites 43,280 11.1

Viacom Digital 42,572 11.7

FACEBOOK.COM 31,107 5.1

AOL LLC 30,992 7.4

Amazon Sites 27,169 2.6

*Rankings based on video content sites; excludes video server networks. Online video includes both streaming and progressive download video.

Top Video Ad Networks by Potential Reach

In November, Tremor Media ranked as the #1 video ad network with a potential reach of 85 million viewers, or 49.8 percent of the total viewing audience. Advertising.com Video Network ranked second with a potential reach of 80 million viewers (47.1 percent penetration) followed by YuMe Video Network with 73 million viewers (43.0 percent).

Top U.S. Online Video Ad Networks by Potential Reach of Unique Viewers

November 2009

Total U.S. – Home/Work/University Locations

Source: comScore Video Metrix

Property Unique Viewers (000) Viewer Penetration

Total Internet : Total Audience 170,647 100.0%

Tremor Media - Potential Reach 84,977 49.8%

Advertising.com Video Network - Potential Reach 80,403 47.1%

YuMe Video Network - Potential Reach 73,419 43.0%

SpotXchange Video Ad Network - Potential Reach 66,090 38.7%

BBE - Potential Reach 55,562 32.6%

BrightRoll Video Network - Potential Reach 49,754 29.2%

TidalTV - Potential Reach 39,944 23.4%

ScanScout Network - Potential Reach 33,531 19.6%

Digital Broadcasting Group (DBG) - Potential Reach 26,283 15.4%

Nabbr - Potential Reach 17,646 10.3%

Other notable findings from November 2009 include:

The top video ad networks in terms of their actual reach delivered were: Tremor Media Video Network with 20.0 percent penetration of online video viewers, BBE with 17.5 percent, and BrightRoll Video Network with 16.6 percent.

84.8 percent of the total U.S. Internet audience viewed online video.

The average online video viewer watched 12.2 hours of video.

128.1 million viewers watched more than 12 billion videos on YouTube.com (94.3 videos per viewer).

38.6 million viewers watched 333.4 million videos on MySpace.com (8.6 videos per viewer).

The average Hulu viewer watched 21.1 videos, totaling 2.1 hours of videos per viewer.

The duration of the average online video was 4.0 minutes.

via November Sees Number of U.S. Videos Viewed Online Surpass 30 Billion for First Time on Record - comScore, Inc.

December Data on Facebook’s US Growth by Age and Gender: Beyond 100 Million

December Data on Facebook’s US Growth by Age and Gender: Beyond 100 Million Facebook has been steadily climbing towards 100 million monthly active users (MAU) in the United States, and it finally reached the milestone late this past month, according to the self-reported data in its advertising tool.

Here’s a closer look at how those numbers break down by age and gender. Be sure to check out the caveats for these numbers at the end of the article — the short of it is that you should take all of these numbers as estimates.

Overall, growth appears to have continued at around the same rate as before: Nearly 5 million users joined the site in December, pushing the total from 98.1 million MAU to nearly 103 million MAU. The previous two months saw increases of around 4 million apiece.

Women, especially younger women, continue to comprise the single largest demographic groups within the US. In total, women constitute over 56% of the overall Facebook population — a continuation of a long-time trend.

Younger users saw the biggest numerical increases in December and the 26-34 range saw the largest overall increase, adding 839,000 new MAU, most of whom were female. Earlier last year, we were seeing stronger relative growth in older demographics. Maybe Facebook is facing challenges retaining older users?

In terms of growth rates, younger people and older men saw the fastest growth, as you can see below, with women over 55 not joining the site as fast as they had been earlier last year. In December, men over 55 on Facebook grew over twice as fast as women over 55.

As we enter 2010, only 40% of Facebook users are under the age of 25 – 60% are 26 or older, and nearly 20% are 45 are older. While it started as a site for students in a few colleges, American use of Facebook today is very intergenerational.

Note that the total number of users in a given age group is higher than the combined number of males and females within it, and for a couple reasons. One is that not every user designates their gender on Facebook, either by choice or because they forgot to. Another reason is that overall demographic numbers are estimates.

And now for the caveats, as there are significant irregularities in this data. Facebook’s advertising tool typically reports traffic numbers around a month later than what the company sees internally, judging from what we have observed in the past. And, repeated sampling of any demographic within a single day will typically show a few variations for the numbers. For example, when we took a sample from the advertising tool on January 1 to compare against our sample in early December, we saw the following results for the total number of MAU in the US: nearly 103 million but also 99 and nearly 104 million. Problematically, these estimates appear to differ whenever one sorts the advertising tool for a specific demographic, meaning we don’t have a good window into whether or not each demographic is high or low. The best we can do, given the irregularities in the data, is to look at overall trends. So, don’t assume any of these numbers are facts, but rather loose estimates that are better than nothing.

via insidefacebook.com

via December Data on Facebook’s US Growth by Age and Gender: Beyond 100 Million - Susan Beebe's posterous.

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CHART OF THE DAY: Microsofts Decade Of Dominance MSFT, IBM, CSCO, AAPL, GOOG /by @AlleyInsider

Microsoft will close the decade the same as it started, as the worlds biggest tech company, as measured by market capitalization.Will Microsoft still be on top come December 2019? It doesnt look likely. Its a whole different world for Redmond. At the start of the decade, Microsoft seemed invincible. Now, its just trying to catch up as Google and Apple blow past it with search and mobile. Top5TechCompanies-decadecomparison

via CHART OF THE DAY: Microsofts Decade Of Dominance MSFT, IBM, CSCO, AAPL, GOOG.

Infographic: RIT on Social Networking Sites

Infographic: RIT on Social Networking Sites [caption id="attachment_605" align="alignnone" width="300" caption="Click to englarge"]2065_maxsize_625_800[/caption]

via Reporter Online | Infographic: RIT on Social Networking Sites.

Update:  Ashley Hennigan @ROCtoNYC wisely noticed that the RIT Fan page has over 5,000 fans!  (Note: Ashley tweets for @RITAdmissions)

[caption id="attachment_612" align="alignnone" width="300" caption="Click to englarge"]doodle[/caption]

Visualizing the decline of World Empires from 1800-2009 [VIDEO visualization] #data #infographics

Future Cities [visual] - we will control every aspect of our world via social media and personal devices

As telecommunications and technology changes how we live our lives, it is not inconceivable to think that in the near future, we will control every aspect of our world via social media and personal devices. [caption id="" align="alignnone" width="500" caption="Click for larger view"]Future Cities - /by gdsdigital[/caption]

Full article: http://www.americainfra.com/news/future-cities/

via Future Cities by gdsdigital on Flickr.

What’s Cooking on Thanksgiving, Mapped and Ranked | FlowingData

What’s Cooking on Thanksgiving, Mapped and Ranked

Posted by Nathan / Nov 26, 2009 to Mapping / 1 comment

What’s Cooking on Thanksgiving, Mapped and Ranked

Food-wise, Thanksgiving is different across the country. In some places you're going to get a lot of chitterlings and collard greens, while in others, turkey and mashed potatoes. Personally, I'm a big fan of the 10-course Chinese feast, but to each his own.

The New York Times (Matthew Ericson and Amanda Cox), map what's cooking in your neck of the woods based on searches on Allrecipes. The top search, concentrated in the southeast, was sweet potato casserole. I have no idea what that is, but it must be delicious.

Other popular searches include pumpkin cheesecake, green bean casserole, and pie crust.




Catch all top 50 searches here.

[via @MacDivaONA]

Posted via web from Susan Beebe's posterous

Twitter has "refreshed" their Privacy Policy to cover geotagging feature

Refreshed Privacy Policy

As part of rolling out geotagging today we've updated our privacy policy to explicitly include geotagging and to describe the public nature of most of what people post to Twitter. We've tried to keep it short and sweet with lots of real life examples so it's simple to read through. We'll also be letting people know about the new policy via email and @twitter.
Please give the new policy a read and contact us at privacy@twitter.com if you have comments or suggestions.

Posted via web from Susan Beebe's posterous

Twitter Blog - Twitter releases French language version just in time for LeWeb conference!

Nouvelle saveur : Twitter en Français!

Avec l'ajout de la version espagnole du site le mois dernier, de nombreuses personnes ont rejoint les conversations sur Twitter. De plus en plus de personnes twittent en dehors des États-Unis et nous sommes à présent en mesure d'accueillir les utilisateurs de près de 30 pays francophones. Il est maintenant possible de changer les paramètres de langue en français grâce à la participation des traducteurs qui ont contribué à transformer Twitter en une plate-forme de communication véritablement mondiale.

Les twitteurs français peuvent d'ors et déjà suivre des personnes et des sociétés qui leur sont familières. Que vous fréquentiez @lepicerie ou @lopera pour vos sorties gastronomiques, que vous lisiez @LeMondeFR en allant au travail ou que vous écoutiez @theteenagers sur le chemin du retour ou encore que vous soyez fan des @CanadiensMTL, il y a une multitude d'informations utiles à découvrir à tout moment.

Pour voir Twitter en français, il suffit de consulter vos paramètres et sélectionner "français" dans le menu déroulant.

Une dernière chose : une partie de l'équipe Twitter sera à Paris les 9 et 10 decembré pour la conférence Le Web, présentée par @loic. Les spécialistes de notre plate-forme, Ryan Sarver (@rsarver) et Marcel Molina (@noradio) y présenteront, entre autres choses, une session développeurs. Si vous êtes dans la région ces jours-là, n'hésitez pas à nous rejoindre!

Posted via web from Susan Beebe's posterous

How Dangerous Are Motorcycles? via SocialInfoGraphics

Personal story: I survived a 45 mph impact from a 2-ton Pickup truck while driving in the opposite direct at 35 mph. Oh, and I was only 9 years old driving a Yamaha 90 dirt bike on a public road - gotta love my parents for wanting me to "get out there"... yea... great idea. After my 14 hour "humpty dumpty" knee surgery and 1 year of rehab (3 casts later)... I recovered, but still have scars and pain to live with forever.

Posted via web from Susan Beebe's posterous