Cookies help us display personalized product recommendations and ensure you have great shopping experience.

By using this site, you agree to the Privacy Policy and Terms of Use.
Accept
SmartData CollectiveSmartData Collective
  • Analytics
    AnalyticsShow More
    image fx (67)
    Improving LinkedIn Ad Strategies with Data Analytics
    9 Min Read
    big data and remote work
    Data Helps Speech-Language Pathologists Deliver Better Results
    6 Min Read
    data driven insights
    How Data-Driven Insights Are Addressing Gaps in Patient Communication and Equity
    8 Min Read
    pexels pavel danilyuk 8112119
    Data Analytics Is Revolutionizing Medical Credentialing
    8 Min Read
    data and seo
    Maximize SEO Success with Powerful Data Analytics Insights
    8 Min Read
  • Big Data
  • BI
  • Exclusive
  • IT
  • Marketing
  • Software
Search
© 2008-25 SmartData Collective. All Rights Reserved.
Reading: The Influence Economy
Share
Notification
Font ResizerAa
SmartData CollectiveSmartData Collective
Font ResizerAa
Search
  • About
  • Help
  • Privacy
Follow US
© 2008-23 SmartData Collective. All Rights Reserved.
SmartData Collective > Uncategorized > The Influence Economy
Uncategorized

The Influence Economy

Daniel Tunkelang
Daniel Tunkelang
4 Min Read
SHARE

There’s an interesting convergence of two ideas in recent days. On one hand, there’s been a lot of attention to the problem of measuring Twitter authority / influence. On the other hand, there have been efforts, some more serious than others, to monetize the connections established on social networks like Twitter.

Of course, these are flip sides of the same problem: measuring and optimizing value in a social network. Or, as I like to think of it, the influence economy.

I recently proposed a way to measure influence on Twitter–or, more generally, in an asymmetric social network. While the measure is simplistic, it has the virtue of modeling attention scarcity, thus making it resilient to the inflationary effect of people following more people in the hope of reciprocity. I’m quite bullish about it, and looking forward to seeing someone implement it.

Given such a measure, let’s turn to the question of buying and selling friends. If we can measure influence, then we can monetize it, much as content providers monetize their audience’s attention by selling it to advertisers. But, just as content providers destroy their value by spamming their audience…

More Read

My Opinion: NYT wants cyber security to be a divisive issue.
Can Computers Help Humans Communicate?
Survey: SOA delivering; SOAP out, REST in
Detroit’s Tech Renaissance Enhanced by Infrastructure Development
A beehive is a very interesting biosensor: bees disperse from…

There’s an interesting convergence of two ideas in recent days. On one hand, there’s been a lot of attention to the problem of measuring Twitter authority / influence. On the other hand, there have been efforts, some more serious than others, to monetize the connections established on social networks like Twitter.

Of course, these are flip sides of the same problem: measuring and optimizing value in a social network. Or, as I like to think of it, the influence economy.

I recently proposed a way to measure influence on Twitter–or, more generally, in an asymmetric social network. While the measure is simplistic, it has the virtue of modeling attention scarcity, thus making it resilient to the inflationary effect of people following more people in the hope of reciprocity. I’m quite bullish about it, and looking forward to seeing someone implement it.

Given such a measure, let’s turn to the question of buying and selling friends. If we can measure influence, then we can monetize it, much as content providers monetize their audience’s attention by selling it to advertisers. But, just as content providers destroy their value by spamming their audiences with ads, influencers stand to destroy their own value by selling out.

But, as the saying goes, everyone has a price. It may be crude, but we can certainly compute how much influence X gains from Y following X–as well as how much Y’s value as a follower decreases through the dilution of Y’s attention. Thus, if X wants Y as a follower, perhaps X should offer Y compensation that reflects X’s gain and Y’s loss.

I haven’t yet worked out the math, but it seems straightforward. And it might even translate into a business model for Twitter and other social networks. By supporting real value creation in the network, an online social network is in the best position to demand a cut of that value as a commision.

Link to original post

Share This Article
Facebook Pinterest LinkedIn
Share

Follow us on Facebook

Latest News

image fx (2)
Monitoring Data Without Turning into Big Brother
Big Data Exclusive
image fx (71)
The Power of AI for Personalization in Email
Artificial Intelligence Exclusive Marketing
image fx (67)
Improving LinkedIn Ad Strategies with Data Analytics
Analytics Big Data Exclusive Software
big data and remote work
Data Helps Speech-Language Pathologists Deliver Better Results
Analytics Big Data Exclusive

Stay Connected

1.2kFollowersLike
33.7kFollowersFollow
222FollowersPin

You Might also Like

Lots of Search News Today!

5 Min Read

3 Things that Are Still Preventing Businesses from Adopting the Cloud

5 Min Read

If I Told You a Fractal Solution, Could You Change the CEO’s Mind?

7 Min Read

SAP and Teradata Announce Partnership

0 Min Read

SmartData Collective is one of the largest & trusted community covering technical content about Big Data, BI, Cloud, Analytics, Artificial Intelligence, IoT & more.

data-driven web design
5 Great Tips for Using Data Analytics for Website UX
Big Data
giveaway chatbots
How To Get An Award Winning Giveaway Bot
Big Data Chatbots Exclusive

Quick Link

  • About
  • Contact
  • Privacy
Follow US
© 2008-25 SmartData Collective. All Rights Reserved.
Go to mobile version
Welcome Back!

Sign in to your account

Username or Email Address
Password

Lost your password?