Netbadges will introduce new types of Netbadges. Right now we only award the "Bridge Builder Badge" for being the most like a bridge (max value of the Betweenness Centrality score). Next we may award the "Newcomer" or "Hub" award.
NodeXL: more content analysis (see recent maps for examples of summaries of top URLs, Hashtags, and @usernames mentioned in each group in the network). We will focus on ease of use and access to data sources (G+ importer coming in a week or two, for example).
NodeXL will focus more on Time. Animation and better analysis of change and contrast between networks is coming.
When NodeXL is set up to run automatically, I mostly just look at the contents of its report output directory (which is synched to all my machines via Dropbox). I just look at the most recent maps and reports. In minutes I can review 100+ maps.
Sorry guys, lost my 'Net connection for a moment. Case that happens again, I want to be sure to sneak one more question in: Marc, so you've got Netbadges and NodeXL. What's missing? Or, maybe I should say, what's next?
We have learned a lot about structure and social media. The variations you can see in Graph Gallery are one example. Also see the collection flickr (the images are higher resolution in flickr): http://www.flickr.com/photos/marc_smith/sets/72157622437066929/
The shapes we see often are "broadcast", "community", "brand", "polarized".
Our current focus is on automating the process from end to end. These maps are now automatically collected, analyzed, visualized and published with a text summary. The results are what you can see in some of my maps in NodeXLGraphGallery.org. We want to make it so that making a network map is as easy as making a pie chart.
Marc, being a dashboard geek, I was wondering if you ever keep any on-going 'dashboard-style' observations of any particular social media sites? Something that you keep an eye on over a period of time?
What should you do when you know the mayor of your hashtag? Yes, in some cases it is at least a good idea to follow them. They may follow you. You may even want to judiciously retweet them. They will almost certainly follow you then. And you may find that over time your tweets get greater visibility among these influential (there I said it) folks.
So Marc, this might not be something you're privy, to but when they do find out who the "mayor of the hashtag" is -- then what? Do they try to influence that person, and use further mapping to measure success, for example?
Shawn: volatility is an issue that can be addressed by controlling the history window. We like volatility if we want "instantaneous" data - who is the center of the conversation *NOW*. But we may also want to know about the centrality of people over a longer window, to rule out infrequent fluctuations. These measures are based on whatever you feed them.
Collective action dilemma theory is a useful framework for describing phenomena like wikipedia, message boards, photo archives, where many contribute to assemble and author the material and even more people come and take from the resource (often without ever making a contribution). The magic of the Internet is that it reduces the size of the "minimal contributing set" - the fewest number of people needed to generate a resource, while increasing the ability of a group to find each other, and simultaneously making the resources reusable and findable. That is a lot to change for a social process!
Marc. How permentant are these centralities? Google and Kout ranks take time to change. But exporting data from Twitter on NodeXL or badges on a topic on Netbadges, how different could my results be day to day?
Flexible Import and Export Import and export graphs in GraphML, Pajek, UCINet, and matrix formats.
Direct Connections to Social Networks Import social networks directly from Twitter, YouTube, Flickr and email, or use one of several available plug-ins to get networks from Facebook, Exchange and WWW hyperlinks.
KenAa: Prediction is a often sought goal. I have questions about the predictive value of social media. I think social media is largely reactive. But reactions can be predictive, so I do not rule out its potential there. But many want to, for example, predict the US Presidential race with "Tweet" votes.
Marc, regarding a macro-socialogical topic such as 'Collective Action' in regards to social media analysis, have you encountered techniques that would enable one to predict events like 'flash mobs' (maybe there's an emergant metric that indicates this). This would probably be based on twitter data...
Have a look at NodeXLGraphGallery, compare a number of the maps. Note how they vary in terms of the ratio of isdolates. The maps with many isolates represent topics that could be called "brands" or "pubic" topics.
Yes, when you want to change an entrentched belief about the product or service, the hubs are important.
But even there, the hubs may have less value than the bridges.
So, I am simply advocating for the use of more measures of network location and the inclusion of more locations in the network as having possible value - all depending on your goal. It is just that the goal is not *always* get the big shot to talk about me.
Marc. Not sure if we got to Ning Song's question, but wanted to insert it here. She asks: what are the main fields where social network analysis applied? in addition to customer sentiment analysis and fraud detection?
Most influencer scores suggest that hubs with many links are the most valuable people. And they are valuable. If you want to get a new message out to your existing customers the hubs are great broadcasters. But they are likley to already be a customer, and thus have little to add in terms of new business.
But I will argue that for the strategic goal of "new customer acquisition" the isolate is the most "influential" person in the room. They have no connections to your community but they just said your name.
It also seems to me that if one wanted to pay attention to geographical location, another option might be to use a place name as a keyword or phrase. This might be particularly usefuil with smaller communities where people using the name, say on Twitter, would likely be residents.
Marc, can you explain about the lat/long? Does that mean you get coordinates from a Tweet but that Twitter users themselves do not generally mention where they're tweeting from? If you've got lat/long does the absence of location mention in a Tweet matter?
Marc, since you bring up "geography," I'm wondering if you can overlay physical maps on top of the virtual maps NodeXL creates, enabling you to pinpoint geographically where influence originates to where it spreads?
Bridges may have fairly few connections, but their connections matter more since they have the few links to some other group. Social media is a collection of islands of conversation. If you want to jump from cluster to cluster, you need bridges.
It's seems Beth and I are on the track here. As a side discussion, Marc and I were talking about some of the tools we'll be talking about. Maybe you'd like to bring us up to speed on some of the tools you've developed as folks arrive, Marc.
If anyone has already signed in and would like to start sharing some questions on some of the online networking tools shared in the post. You can start doing that now as we get the conversation started.
Here's where we will chat with Marc A. Smith, a sociologist specializing in the social organization of online communities and in other computer mediated interaction. He is co-founder of the Social Media Research Foundation. The organization develops tools to measure and analyze the connection and construction of social media communities.