The Many Forms of Influence

Mitch Ratcliffe, over at BuzzLogic, posts about a number of aspects of online influence. Part of BuzzLogic's approach is to do with the changes in influence over time. One thing that I don't believe is captured in Mitch's post is the distinction between atopical influencers and topical influencers. In other words, there are people who have high standing in the blogosphere, and when they post on a topic that isn't even in their domain, they have huge influence. A canonical example, of course, is Jeff Jarvis and the whole Dell Hell saga. Part of what I believe is going on there is that certain broad topics in the blogosphere are connected to the rest of us as a whole in such a way as to promote the influence of the bloggers. I've posted a number of times some experiments that suggest this type of thing (here is an example).

The notion of topical influence captures the idea that within a particular domain, that person is influential. Engadget might be a good example of this.

These are just two aspects of influence - there are many more.

It is always pertinent, when discussing influence - and influence based analysis, that one should maintain two models of the blogosphere. The first is the networked, influence rich model (which BuzzLogic is promoting). The second is the data driven, signal based model. In this second model, rather than Jeff Jarvis being the sole type of threat to a brand, 1, 000 LiveJournalers who each express independently some dissatisfaction with a product, a movie, etc. within the same timeframe are equally important. There is a signal in the data as a whole that is of vital importance to the brand being monitored.

An illustration of something of this view is the discussion around The Illusionist. In this case, there is no clear online influencer out there shaping the reaction to the movie - what we are seeing is a reflection of offline activity manifesting as a record of individuals' experiences and their propensity to recommend the movie. Monitoring this type of thing requires comprehensive data coverage.

Finally, I would also comment that it is sometimes the story or message that has influence - this is something closer to a true meme - an idea that due to some intrinsic quality will make itself spread between nodes in the network.

Comments

[Mitch Ratcliffe]

Good points all, and the team at BuzzLogic is seeking to identify many faces of influence, but we've found it is best to start with the aspects most familiar to the market and let them digest those. That said, we're addressing both the models you suggest are necessary, providing, for lack of a better description, a meme-level tracking component that shows the rising and falling occurrence of an idea as well as the node-influence of an author like Jeff Jarvis (BuzzLogic's birth came from a pre-Dell Jarvis encounter by a friend of mine, btw).

"Within a timeframe" is an absolutely key notion, we agree. Our system provides longitudinal analysis of user-defined timeframes, not just an atemporal view of the network.

But we also have discovered that within those 1,000 hypothetical posters, whether on LiveJournal or across multiple sites, there are parties that lead the movement, so to speak, and others who spread the message. To some degree there are patterns that repeat within those large phenomena that can be used to identify where to participate as a marketer. That is not to say, however, that the same people always play the same role, rather statistically it is possible to identify within those movements who is currently taking a leadership role.

[Jeff Jarvis]

As much as I would love to be canonical -- just because it sounds so important -- I will have to argue that the Dell saga was really just a coming together of your fabled 1,000 Livejournalers. I have a small public. The proportion of that public, that regular circle of readers and writers, who had Dell problems was even tinier. And I have long argued with absolutely no false modesty, if I do say so myself, that I was not an influencer on Dell. I was merely a convenient point of coalescence. There were 1,000 metaphoric Livejournalers out there, all tearing their hair out at Dell, and they were floating around, waiting -- whether the knew it or not -- for the chance to join together with other miserable sods suffering the same headache. I merely happened along. Links led to links. And an army was formed, almost instantly. This had nothing to do with me or with my small cadre of media blathering friends. It has everything to do with atoms attracting into molecules; it's a magnetic effect I hope I'll soon see in a time-based view of one of your maps: The making of a meme.