Michael Wu, Ph.D. is Lithium's Principal Scientist of Analytics, digging into the complex dynamics of social interaction and online communities.
He's a regular blogger on the Lithosphere and previously wrote in the Analytic Science blog. You can follow him on Twitter at mich8elwu.
Recently, there has been a lot of buzz around the term "influencer." This is partly due to the launch of Fast Company's Influence Project. Beside this project, there is another unrelated project with a very similar name: The Influencer Project, which was also launched around the same time. And yesterday, I gave a webinar at WOMMA on the topic of Influencers and WOM marketing. My presentation is on SlideShare (which fail to convert the animations in the deck); a fully animated version of the slide show is linked at the end of this article as attachment.
Since I’ve done quite a bit of research and written many blog posts on topics related to influencers, I thought it would be nice to collect these posts together in a single spot. This would facilitate the sharing and distribution of these articles, which I am asked about frequently these days. I’ve created a word cloud (via Wordle) for these posts, so if the topics in the word cloud look interesting to you, then you will enjoy this collection. Aside from listing the posts, I will add some commentary to these articles along the way.
The first set of four articles introduces a simple model of the influence process (or simply influence model). This model emphasizes the importance of the target when identifying influencers. It also gives us six necessary factors (i.e. credibility, bandwidth, relevance, timing, alignment, and confidence), which must all be accounted for in order to achieve true influence.
The next set of three posts is on the application of the influence model. Following the principles of this model, I’ve devised a step by step procedure for identifying influencers in interest-oriented online communities. The implementation of the influencer identification algorithm involves heavy use of social network analysis (SNA) and various SNA metrics. Using SNA and social graph visualization, I was able to discover some interesting insights within the communities from our client base.
If you are unfamiliar with SNA, the following two posts offer a very basic introduction and an application of several SNA metrics for characterizing different types of influencers.
Finally, the last two articles are on Fast Company’s Influence Project. Since this project has stirred up much controversy in the industry, there are a lot of very provocative discussions and debates in the comment section. The comments in these two posts are probably much longer and more interesting than the post itself.
Alright, that is what I’ve written on influencers so far. This topic is so deep and important that people start companies (e.g. Klout) just to find the influencers. There is certainly a lot more research that needs to be done, and it is very likely that there will be another chapter on this topic later. But for now, enjoy this self-contain collection of article on influencers. Again, comments, questions, discussion, as well as criticisms are all welcomed as usual. You may comment here or on the comment section of the respective posts. See you next week.
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