Influence is not Authority

Let's imagine we have three blogs: A, B and C. A has 10, 000 readers, B has 100 readers and C has 10 reader. Let's also characterize the topics that these blogs write about. A writes about topics t₁, t₂, ..., t₁₀, B writes about t₅ and t₆ and C writes about t₅ only.

Now, suppose C writes something interesting on topic t₅ and both A and B links to this post adding their own particular commentary. Who will drive more traffic to C? A or B? While A has many more readers than B, it is topically a very broad blog. The writer doesn't have the time (or expertise) to really go deep into the issues of all these topics. Consequently, her audience is not made up of experts in those areas and reads there to get a high level picture over a broad range of topics. On the other hand, B's readers pretty much just go there for 2 topics. B has time to go in to detail and understand those topics and is probably spending plenty of off line time in that topical space as well. Consequently, B will actually send more traffic (not relatively more, but absolutely more) to C than A will due to the specialization of his audience.

What I'm describing above is the difference between some notion of popularity (which may be called influence) and some other notion of authority (or expertise) and how these issues are related to both the blogger (blog) and the readers of that blog or feed. Measuring readership on topics is key to really modeling this stuff in social media which is why FeedBurner is such an asset to Google. It also captures why metrics for bloggers should capture notions of topic (something which BuzzLogic understands).

[Thanks to Akshay Java for discussions that highlighted this issue.]

Comments

[Pierre]

I think that in your post you forget some very important things..
Things can be totally different.. depends on:
- at what time the post will be or the links will be.. (if you speak about Wall street, a link or post has more chance to be popular just when Wall Street is going to open than @ 3 pm)
- the potential of readers of the topics (if topic 5 is about football, i am not sure than B will bring more than C.. if topic 5 is about warrants in russian bonds, OK.; B will bring more
- time when you look at that.. For exemple during Summer, if topic 5 is about skying, C will bring more than B because more people in C will be surprised by topic about sky in Summer.; In winter, it will be B

What do you think about that ?

[Elihu Vedder]

Brian Ulicny and his colleagues have written two papers on distinguishing blog credibility from blog authority/influence (measured by inlinks), one of which was at ICWSM'07. See their discussion of the authority/credibility split between 'Zeus Bhagwan' writing about the 'Gospel of Judas' on News is Now Public' and the credibililty/authority of James Davila on paleojudaica.blogspot.com:

B. Ulicny, K. Baclawski and A. Magnus, New Metrics for Blog Mining, Proceedings of SPIE -- Volume 6570 Data Mining, Intrusion Detection, Information Assurance, and Data Networks Security 2007, Belur V. Dasarathy, Editor, 65700I (Apr. 9, 2007), Orlando, FL. http://vistology.com/papers/VistologySPIE07.pdf

B. Ulicny andK. Baclawski, New Metrics for Newsblog Credibility, Proceedings of 1st International Conference on Weblogs and Social Media (ICWSM'07). Boulder, CO.
http://vistology.com/papers/VIStologyICWSM07poster.pdf

[Joshua O'Madadhain]

I have some unpublished work on this which looked into tracing influence via similarity in topic models (generated by LSA or its successors, e.g., Blei's LDA) of cited documents; it would be pretty easy to add traffic into the model. Of course, it appears that now I need to read Brian Ulicny's work to catch up...

There's also a paper or two by Lada Adamic and others, which are available on her publications page: http://www-personal.umich.edu/~ladamic/publications.html

It does seem to me that there may be a few factors which are being conflated here, though. One is the probability that any given reader will follow a link presented in the blog. If I think that the authors of blog A generally provide useful/interesting links, I'm more likely to follow them. Similarly, if A's topics match my interests, I'm more likely to follow their links. Finally, if A does a really good job of covering the topics that they bring up, I may be _less_ likely to follow their links.

Granted, if A's topics are 'broad' (i.e., quasi-uniformly distributed in topic space) then it's more likely that some of their links will not be of interest to me, especially in the absence of any information on my interests. But if you have any way of modelling the interests of the visitors (e.g., looking at the topics of referring pages, or of their own blogs if you've got a blog URL, etc.), then it could be very interesting to model the probabilities in terms of topic/interest similarities.

Thanks for the post.

[cicicocuk]

thanks you all
think that in your post you forget some very important things..
Things can be totally different.. depends on:
- at what time the post will be or the links will be.. (if you speak about Wall street, a link or post has more chance to be popular just when Wall Street is going to open than @ 3 pm)

[resim]

thanks you all
think that in your post you forget some very important things..
Things can be totally different.. depends on:
- at what time the post will be or the links will be.. (if you speak about Wall street, a link or post has more chance to be popular just when Wall Street is going to open than @ 3 pm)