, • EMC • email@example.com
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Networking is naturally a central focus of the Internet computing space. Initially, this term referred to connecting computers together, but today it refers just as often to how people are interconnected — that is, "social networks." I discussed information overload in the context of social networks such as Twitter in a previous column. 1 This issue, I discuss three other social networks: Facebook, LinkedIn, and Google Wave — yes, I know that Google Wave isn't exactly a social network — and I offer my own prediction of where I think things in this space might go.
Facebook is, of course, a darling of the Internet. It's immensely popular, not only among college and high school students but also their parents and grandparents. As someone who is many (many) years past any type of school, I've really enjoyed reconnecting with former classmates I had completely lost touch with. In some cases, I've connected with classmates I didn't even know at the time.
The more friends you have on Facebook, the more inundated you're likely to get with their updates, if you decide to brave the system and look at the updates at all. My comments about Twitter 1 apply, on the whole, to Facebook: the more your feed includes posts from public sources such as news media and celebrities, the more noise there is. But even private entities can be "noisy," so what am I to do? I can block people in their entirety or block random applications (Farmville, you're GONE!), but I have little opportunity to prioritize and be sure that the updates from the small handful of people I really want to keep in touch with aren't lost. For the most part, I've addressed this by tracking an RSS feed on links posted by certain people, and watching them completely outside of Facebook. Mostly, I just ignore things because I can't separate the wheat from the chaff.
Even so, the noisiness of the system has some nice touches. As I write this, I'm recuperating from a nasty leg injury I incurred a couple of nights ago. I posted something to Facebook about how I was about to see an orthopedist to see just how badly I'd injured myself — since I could barely walk at the time I feared the worst. By the time I got back from the doctor to report that it wasn't as serious as I'd feared, I already had over a dozen messages from people asking for more details, reassuring me that the nasty outcomes other people were guessing were probably wrong, and so on; I got a few more comments to my update about what I'd been told. The key here is that many of these comments were not from close friends (at least not at present) but from a broad spectrum of past and present friends and acquaintances. I frequently see other, similar threads, where people comment on an update to offer moral support, and I believe the psychological impact of these sorts of reassurances and communal outpouring of encouragement can't be overstated.
Whereas Facebook tries to be all things to all people, including public message exchanges, photos, games, music, and so on, LinkedIn has had a much more targeted approach. I joined several years ago because it seemed innocuous enough, but not because I expected to actively mine it for professional use.
At this point, I've used LinkedIn in its three obvious roles: as the recipient of an inquiry, such as a job hunter contacting me to apply within my organization; as an intermediary, passing messages on behalf of friends (or friends of friends) along my network; and as a job hunter myself. I can attribute my current position directly to LinkedIn because I identified a company of interest but wasn't aware of anyone I might know there until I used LinkedIn to search for a connection. (The company I joined was relatively small and was acquired by a much larger company shortly after I arrived.) It turned out I had known one of the founders for many years.
LinkedIn is trying to expand its presence by adding more applications, basically becoming more like Facebook. To be honest, if I want to know that someone is going on a trip, I'll check them on Facebook, but if I want to connect with someone professionally, LinkedIn is the place to do it. Please don't change.
Google Wave ( http://wave.google.com/help/wave/about.html) is another form of social network entirely, if it can be called a social network at all. It's described as "an online tool for real-time communication and collaboration," a combination of conversation (like email) and document (because messages can embed a wide range of rich media as well as interact with agents that can perform services such as real-time translation, notification, and so on).
I view it as a social network because it's an enclosed community. I can only interact with others on the system I have a direct connection with. When I started, this was an extremely limited list, only a few people including the person who'd invited me, but it's grown over time.
Many people have told me they tried it out and then stopped using it, for any of a variety of reasons. These include the smallness of the community (recall Metcalfe's Law — the more users or systems on a network, the more useful it is; http://en.wikipedia.org/wiki/Metcalfe%27s_law), some performance issues in the early prototype, and in some cases a general dissatisfaction with the current paradigm. So why was there so much hype about the system that people were begging to be let in? In fact, I started wondering if it had been compared to "The Emperor's New Clothes" and wasn't surprised to find a blog to that effect ( www.markevanstech.com/2009/10/24/google-wave-the-emperors-new-clothes).
Let me give my own impressions of Wave, with the caveat that I've only been using it a couple of months, and it's in "preview" mode.
Some things about the system (as it stands in early December 2009) are quite surprising to me. A key example is the notion that anyone in a conversation (a "wave") can edit the wave anyplace in it, but the only indication that an update has occurred is in the list of waves. If the edit isn't at the very end of the wave, I have to replay every edit from the start to see the most recent one. Replaying one of my waves takes perhaps a minute for it to load the full history, and only then can I back up one edit to identify the change. What am I missing?
Another common complaint is that the system is, by default, completely interactive. Each character I type is sent immediately to everyone else on the wave if they're active in the system. Not. A. Good. Idea.
Someday, I trust Google will integrate the regular Google mail client, Gmail, with Google Wave. I'd like to have just one list of messages to monitor. Getting email each time a wave is updated is not the solution, by the way.
At the same time, even the emperor eventually put on real clothes. I have little doubt that Google will address these issues (identifying edits efficiently, suppressing interactive updates except when demanded, and so on) soon. Also, although the interface has problems, the underlying Wave API is a really interesting piece of work. As a colleague at Google pointed out, by providing collaboration, history, and federation, Wave enables a new class of applications. We just have to get to that point without turning off the early adopters.
Because this is an issue about Internet predictions, I should make some of my own here.
The trend toward cross-social-network integration will continue, with updates posted to network X appearing magically on network Y. However, the trend toward single networks being all things to all people has to subside. LinkedIn and Facebook are different beasts and should remain so.
Novel applications are the bread and butter of any system. Facebook's novelty appears on the wane; I don't know how many variations of "Farmville" a person will try out, but I don't see radically different uses of the Facebook platform. On the other hand, Wave is just getting started. I think one thing it needs to change, however, is the notion that everyone in a wave sees exactly the same thing. Wave has an automated translation system you can add to a wave, to translate to one specific language, but what about a wave with many people all with their own language? Wave also has a notification agent. However, when added to a wave, it emails every participant rather than the person who added it.
Information overload just keeps getting worse. Too small a network, such as in the first days using Google Wave, leads to an uninteresting experience, but too large a network is also a problem. Some people choose to keep their friend lists small as a way of controlling this overload, but there are other solutions. A personal agent that can learn what I care most about and feed me just that information will be a savior, and it seems like the sort of tool that can greatly benefit from the open source community: once a framework for this sort of filtering is available, people can contribute agents with domain knowledge of all types of information sources ranging from email to RSS feeds to social network updates. Join the cause!
As I enter the final year of my term as IC's editor in chief, I'd like to end my column by thanking the staff and volunteers who make the magazine possible. So, I bid farewell and thanks to our former publications coordinator, Hazel Kosky, and our former managing editor, Steve Woods, both of whom were involved with IC for very many years. I welcome the support of Joel Luber of Allen Press (publications coordinator), Jennifer Gardelle, and Jenny Stout, as well as the ongoing support from Rebecca Deuel-Gallegos. I thank the editorial board for their continued contributions to the magazine, and I especially thank Siobhán Clarke and Michael Rabinovich, the two associate editors in chief, for their hard work and dedication. I also want to call out two of our editorial board members, Vint Cerf and Munindar Singh, for guest editing this issue compiling visions of the future Internet.
Juliana Freire is an associate professor at the University of Utah's School of Computing. Her research interests include development of data management technology to address new problems introduced by emerging applications, including the Web and scientific applications; focused Web crawling; and hidden-Web information discovery, retrieval, and integration. Freire has a PhD in computer science from the State University of New York at Stony Brook. She's the program chair for the World Wide Web Conference 2010, and is a recipient of a National Science Foundation CAREER and an IBM Faculty award. Contact her at firstname.lastname@example.org.
The opinions expressed in this column are my personal opinions. I speak neither for my employer nor for IEEE Internet Computing in this regard, and any errors or omissions are my own. (I thank my various Google Wave contacts for their thoughts on Wave.)