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
    big data analytics in transporation
    Turning Data Into Decisions: How Analytics Improves Transportation Strategy
    3 Min Read
    sales and data analytics
    How Data Analytics Improves Lead Management and Sales Results
    9 Min Read
    data analytics and truck accident claims
    How Data Analytics Reduces Truck Accidents and Speeds Up Claims
    7 Min Read
    predictive analytics for interior designers
    Interior Designers Boost Profits with Predictive Analytics
    8 Min Read
    image fx (67)
    Improving LinkedIn Ad Strategies with Data Analytics
    9 Min Read
  • Big Data
  • BI
  • Exclusive
  • IT
  • Marketing
  • Software
Search
© 2008-25 SmartData Collective. All Rights Reserved.
Reading: A Twitter Analog to PageRank
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 > A Twitter Analog to PageRank
Uncategorized

A Twitter Analog to PageRank

Daniel Tunkelang
Daniel Tunkelang
4 Min Read
SHARE

A few weeks ago, there was a flame war about Twitter authority, and I was all too eager to throw fuel on the pyre. But now that the blogosphere has calmed down a bit, I’d like to propose a ranking measure that I think might work. My apologies if it isn’t original. In fact, if you’ve seen it elsewhere, please point me to it.

Let me start with the assumptions about the model:

  • Influence(X) = Expected number of people who will rea…

More Read

More music to the ears of SOA enthusiasts
What’s strategic for Google?
Tips on surviving R
Using busines rules in stable, core processes
Even Google Should Beware Of Hubris

A few weeks ago, there was a flame war about Twitter authority, and I was all too eager to throw fuel on the pyre. But now that the blogosphere has calmed down a bit, I’d like to propose a ranking measure that I think might work. My apologies if it isn’t original. In fact, if you’ve seen it elsewhere, please point me to it.

Let me start with the assumptions about the model:

  • Influence(X) = Expected number of people who will read a tweet that X tweets, including all retweets of that tweet. For simplicity, we assume that, if a person reads the same message twice (because of retweets), both readings count.
  • If X is a member of Followers(Y), then there is a 1/||Following(X)|| probability that X will read a tweet posted by Y, where Following(X) is the set of people that X follows.
  • If X reads a tweet from Y, there’s a constant probability p that X will retweet it.

This model is obviously simplistic in all three assumptions. But I think it’s a reasonable first cut. In particular, it accounts for the inflation that occurs from people who follow in the hopes of reciprocity. There’s less value in being followed by someone who follows a lot of people, because that person is less likely to read your messages or retweet them.

Of course, there’s room for adding more realism to this model, but I hope it is at least close enough to the truth to be interesting.

From this model, it’s easy to measure someone’s influence recursively, assuming that we know the constant retweet probability p:

equation1

The recursion is infinite over a graph with directed cycles, but rapidly converges as high powers of p approach zero. I would think this measure wouldn’t be hard to compute to a reasonable accuracy.

This measure strikes me as a PageRank for Twitter or any system with similar properties. There’s more room for nuance, but I at least find this approach more plausible than the ones I’ve seen. It also strikes me as hard to game, since it isn’t counting retweets, and it’s hard to add much influence through followers who don’t have any influence themselves.

What do folks think? Has anyone tried this? If not, is there anyone who’d like to try hacking an application to compute it? Either way, please let me know!

Link to original post

Share This Article
Facebook Pinterest LinkedIn
Share

Follow us on Facebook

Latest News

AI role in medical industry
The Role Of AI In Transforming Medical Manufacturing
Artificial Intelligence Exclusive
b2b sales
Unseen Barriers: Identifying Bottlenecks In B2B Sales
Business Rules Exclusive Infographic
data intelligence in healthcare
How Data Is Powering Real-Time Intelligence in Health Systems
Big Data Exclusive
intersection of data
The Intersection of Data and Empathy in Modern Support Careers
Big Data Exclusive

Stay Connected

1.2kFollowersLike
33.7kFollowersFollow
222FollowersPin

You Might also Like

The R Journal – A Refereed Journal for the R Project Launches

3 Min Read

Is Enterprise 2.0 a Crock?

6 Min Read

Clean Your Data Like You Clean Your Undies

6 Min Read

Looking for a Devil’s Advocate

4 Min Read

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

ai is improving the safety of cars
From Bolts to Bots: How AI Is Fortifying the Automotive Industry
Artificial Intelligence
ai in ecommerce
Artificial Intelligence for eCommerce: A Closer Look
Artificial Intelligence

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?