Issue link: https://read.dmtmag.com/i/78956
Social Networks: Is Spatial Special When It's Social? EDGENODES M BY NIGEL WATERS ore than 10 years ago, Frances Cairncross suggested in his widely cited book, The Death of Distance: How the Communications Revolution is Changing Our Lives, that the social and economic changes being wrought by computers and associated communications technology such as the Internet and cellular phones would be as influential as the other two great revolutions in transportation: the railway in the 19th century and the automo- bile in the first half of the 20th century. In many areas, such as the delivery of government services, Cairncross suggested that the full impact of these changes might take "a generation or two." But he couldn't have foreseen the influence of one additional innovation: social networks (SNs). In the 15 years since the first edition of Cairncross' book was published, SNs have become a global influence on all forms of economic activity. The origins of SN Web sites may be traced back to the founding of Live Journal and Blogger in 1999. As might be expected, current lists of SN sites can be found on the Internet, and one of the most comprehensive lists can be found on Wikipedia. This alphabetical list provides information on each site's focus, the date launched, number of registered users, the type of registration (i.e., whether registra- tion is open or restricted and how it's restricted) and the Global Alexa page ranking (www.alexa.com). Nigel Waters, editor of Cartographica, is a professor of geography and director for the Center of Excellence for Geographic Information Science, George Mason University; e-mail: nwaters@gmu.edu. 12 Measuring Influence The importance of SN sites to the global economy can be determined by noting that three sites on Wikipedia's list are ranked in the top 15 of all Web sites worldwide (Facebook, 2; Twitter, 8; LinkedIn, 12), but this is somewhat misleading, as the list doesn't include an Alexa ranking for Qzone, the world's second-largest SN site, based in China. The Social Media Influence (SMI) Web site presents an imaginary map ( socialmediainfluence.com/wp-content/ uploads/2012/06/SMI_socialmedia_map.jpg) that groups SN Web sites into the following "islands": 1. The Democratic Republic of Commerce/People's Republic of Engagement 2. Analytics Archipelago GEO W ORLD / AUGUST 2O12 3. Isle of Social Gaming 4. So-Lo-Mo (Social-Local-Mobile) 5. Island of Enterprise/Consultania 6. Isles of Influence 7. Platformia (the center island featuring sites such as Facebook, Twitter, LinkedIn and YouTube) Obviously, this categorization is somewhat "tongue in cheek," but the list is useful and includes many sites that aren't on the main Wikipedia list. In more prosaic terms, the categories are engagement, analytics, gaming, social business, commerce, influence and generic platforms covering "all of the above." The SMI and Wikipedia lists differ, with several sites only found on one list. The Social Network Workshop In December 2010, the National Center for Geo- graphic Information and Analysis held a workshop to establish a research agenda for determining the spa- tial and temporal constraints on SNs. Apparently, the center also was concerned that SNs would render distance irrelevant. Perhaps it additionally was concerned that no current GIS software provides the means to analyze influence within an SN. It's the network's structure—topo- logical and not geographical space—that creates SN influence. Tobler's celebrated First Law of Geography that "Everything is related to everything else, but near things are more related than distant things" now must be recast: "Everything is connected to everything else, but things connected with fewer links are more related"—and geography may well be irrelevant. In widely cited research conveniently summarized in their 2009 book, Connected: How Your Friends' Friends' Friends Affect Everything You Feel, Think and Do, Nicholas Christakis and James Fowler demonstrated that individuals within social networks are influenced to a diminishing extent by other individuals who are divided by up to three degrees of separation. For example, they have shown that it's your friends, and your friends' friends and even your friends' friends' friends that influence whether you're obese, happy, have a heart attack, catch the flu, start or quit smoking, and many other aspects of your socio-economic behavior. How do you analyze that within a GIS? Naturally, the SN Workshop provided a series of position papers (www.ncgia.ucsb.edu/projects/ spatio-temporal/participants.php) and a final report (www.ncgia.ucsb.edu/projects/spatio-temporal/ docs/workshop_report_final.pdf) that attempts to do just that. Kathleen Carley, for example, provided a brave attempt to link network and geographic space. Sometimes there was too much geography and
