Data Science

Health Factor 5: Interaction

Interaction.jpgThis is the fifth blog in the miniseries on the Health Factors of CHI. Other blogs already in this miniseries are:

  1. Traffic
  2. Content
  3. Members
  4. Liveliness

Last time we talked about the most troublesome predictive health factor: Liveliness. This time we will discuss Interaction.


The Interaction Health Factor

When you are able to create a lively community, the hard work is half done because by definition a lively community has solved a difficult conundrum of participatory media: How do you get people to participate? However, in a healthy community, it is not enough just to participate. There must be interaction with other users. Otherwise, where is the social of social media?


There are two important dimensions to interaction:

  1. The amount of conversation you have with a particular user.
  2. The number of different users you've communicated with.

Clearly, the more you talk to a user, the more interaction you have with that user, but talking to different users also increases the level of interactions within your community. In fact, the latter has a greater effect on the overall health of the community. The interaction health factor measures the average number of unique participants per topic weighted by the amount of conversation between them. Thus, this health factor provides an estimate of the average number of members a potential user is likely to interact with and the estimated amount of messages that will be exchanged between them. Accordingly, this health factor may be interpreted as the expected scope of the engagement for potential visitors.


Different Modes of Interactions on the Lithium Platform

Because different communities have vastly different kinds of interactions, the interaction health factors also vary greatly across communities. For example, the dominant mode of interaction of a support community consists of a troubled user asking a question and a knowledgeable user answering the question. This kind of interaction usually involves few users with relatively short diagnostic dialogs before arriving at the solution, so support communities tend to have a steady and modest value for the interaction health factor. In contrast, the dominant mode of interaction for an enthusiast community often involves extended discussions among many users. Also, because the topic and amount of discussion is usually event-driven, enthusiast communities tend to have a higher, but more volatile value for their interaction health factor. B2B and internal communities also tend to have lower level of interactions than that of enthusiast communities.


The Current and Future of Interaction

Besides the difference in community purpose, the different web applications, such as forums, blogs, ideas, and tribal knowledge base (TKB), also have drastically different modalities of interaction. However, the current health factors and CHI were developed based on analyses of primarily forum interactions. Blogs, Ideas, and TKB are relatively new products in our platform that do not have 10 years of historical data. Consequently, the expected level of healthy interaction in the current algorithm may be too stringent for these new interaction modalities. As a result, the interaction health factor for communities that use these new applications may appear slightly lower than expected. We have made note of this issue and we will address it in the next revision of our formulae.


I hope this blog gave you a better understanding of interaction and addressed the concerns you may have concerning this health factor. Next time, we will move on to the last health factor, responsiveness. Watch for updates at mich8elwu.


Michael, I'm wondering if you could elaborate on how interaction is measured. For example, replying to someone's post is obviously an interaction. But that is probably too narrow a definition, because you and I could be interacting by both replying to a 3rd user's post and having some back and forth, without direct replies to each other. For blogs, this would be the only means of interaction I guess - readers going back and forth with comments. Curios to hear your thoughts on this, and how it is/will be addressed. Thanks! Enjoying all your posts...catching up on CHI.

Data Science

Dear Mike,


The precise calculation for computing the interaction score is done in 2 steps:

1. compute the interaction score for each publically accessible thread in the community.

2. average the interaction score over all publically accessible threads in the community.


So you may ask how do we compute the interaction score for each thread then. Well, that is computed by taking the number of unique participants in the thread, subtract 1 from it, then multiply by the base-2 logarithm of the number of messages in that thread.


If we let u=number of unique participants, and m=number of messages in the thread, the interaction score is (u-1)*log2(m). After we computed this for each thread, we just average them across the community, smooth and normalized to get the interaction health factor for the community for that week.


Few things to notices is that this equation is design this way so when there is only 1 users, the interaction should be zero. And when there are 2 users, each posted 1 message. ie, user A ask a question and user B answer him/her. Then the interaction will (2-1)*log2(2)=1, or 1 unit of interaction.


Also, because the number of message is inside a log2, which is a very slow growing function, whether 2 person talk is more important than how much they talk. The point is that if there are 10 more person join in a discussion then the interaction could increase by 10x for that thread, but if 2 person talked 10x more, then interaction would only increase about 3x.


Hope this is not too confusing. But you wanted me to elaborate...


Concerning the fact that there are many possible interaction. That is true. But CHI is not meant to capture all type of interaction. Besides, since it was intended to be a score that any community (including non-Lithium communities) can compute, I was working with a very limited set of metrics that any community platform should have. That is why I was limited to this simpler form.


I hoep this answered your question... Keep the questions coming.



Yes, that helps. Thanks!


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