Different Kinds Of Twitterers: What’s The Right Balance For Business?

I have been thinking a great deal about the application of the open follower model (a la Twitter) to the emerging social business. My intuitive sense has been that there are many ways that people use Twitter, and these could be discovered by various kinds of statistical analysis, but otherwise the truth of what is going on may be concealed by the buzz of many people talking all at once.

Bernardo Huberman, Daniel Romero, and Fang Wu published a report early this year (see Twitter Under The Microscope: Huberman, Romero and Wu) about Twitter usage, and discovered a key reality: the apparent, superficial social network based on following and followers conceals a deeper, sparser social network, where relationship really matters and where the most critical communications take place.

[from Social Networks That Matter: Twitter Under The Microscope by Bernardo Huberman, Daniel Romero, and Fang Wu]

In conclusion, even when using a very weak definition of “friend” (i.e., anyone who a user has directed a post to at least twice) we find that Twitter users have a very small number of friends compared to the number of followers and followees they declare. This implies the existence of two different networks: a very dense one made up of followers and followees, and a sparser and simpler network of actual friends. The latter proves to be a more influential network in driving Twitter usage since users with many actual friends tend to post more updates than users with few actual friends. [emphasis mine.] On the other hand, users with many followers or followees post updates more infrequently than those with few followers or followees.

Many people, including scholars, advertisers and political activists, see online social networks as an opportunity to study the propagation of ideas, the formation of social bonds and viral marketing, among others. This view should be tempered by our findings that a link between any two people does not necessarily imply an interaction between them. As we showed in the case of Twitter, most of the links declared within Twitter were meaningless from an interaction point of view. Thus the need to find the hidden social network; the one that matters when trying to rely on word of mouth to spread an idea, a belief, or a trend.

This accords well with my intuitions, and suggests that in business, just as in the larger open social context, a small number of relationships will be the place where the most important work gets done, as companies begin to adopt open follower social tools.

A more recent study has been published that slices the Twittersphere from a different angle:

[via Study Reveals Two Types of Twitter Users]

In a study of Twitter, a microblogging service used by millions of people from high school students to national elected officials, Mor Naaman and Jeffrey Boase found that 80 percent of regular users are “meformers,” people who use the platform to post updates on their everyday activities, social lives, feelings, thoughts and emotions. The remaining 20 percent – “informers” – share information, have larger social networks and are more interactive with their followers.

In their report, the Rutgers researchers examined several questions and teased answers from the data:

[via Is it Really About Me? Message Content in Social Awareness Streams]

1. What types of messages are commonly posted and how does message type relate to other variables?
2. What are the differences between users in terms of the types and diversity of messages that they usually post?
3. How are these differences between users’ content practices related to other user characteristics?

The researchers discovered nine categories of messaged (see below) but four were the dominant ones: Information Sharing, 12%; Opinions/Complaints, 24%; Statements and Random Thoughts, 25%; and “Me Now”, which are mood, location, and status updates, 40%.

The researchers used cluster analysis to find that there are really two clusters of users, who can be typified by the distribution of the various sorts of tweets they make. These are “Meformers”, who produce almost 50% “Me Now” messages, and “Informers”, who produce about 50% Information Sharing messages. (Note: these Informers are really wahat I was talking about when I coined Onfovores.)

Meformers make up 80% of the population, while Informers are 20%. Informers have more friends and followers than Meformers, and have a higher degree of mentions by other users in messages. This suggests that Informers would play a stronger leadership role in a business setting, shaping the discussion about events, helping to set context about what is more important, and so on.

But the role of Meformers shouldn’t be discounted. First of all, a great deal of status updates — ‘Just left the budget meeting’ or ‘push the new UI to production’ — isn’t just about the individual, but about actions they are taking in pursuit of work-related aims. In the open follower model this get passed along as a ‘Me Now’ message, but it isn’t navel gazing: it’s social signaling about work activities.

More importantly, every one engages in both ‘characters’ to some extent, although it is very bipolar. It appears that women are more likely to lean toward Meformage than men, but just a bit.

All sociality is based on “me first”, but not in an egocentric way. We are defined by our connections to others, and the first gift we give is a tale of ourselves. And this seems to have occurred to the researchers as well:

Note that although the Meformers’ self focus might be characterized by some as self-indulgent, these messages may play an important role in helping users maintain relationships with strong and weak ties.

Or to indicate the status of work.

My sense is that business needs a mix of these sorts, and it could very well be that the natural 80/20 split that the researchers discovered in their research is a good mix for business. We might as well assume that the natural order of things has evolved to meet some deep social needs.

Maybe we need 20% of the tribe scanning the horizon for prey and predators, tracking the stars and clouds. Meanwhile, the other 80% are working on tools, setting up the tents, milking the goats, and drying the corn.