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By contrast, “community clusters” represent popular topics that may develop multiple smaller groups, many of which form around a few particular hubs, each with its own audience, influencers and sources of information. Pew provides the example of a global news story that attracts different types of coverage from different news outlets, like the New York Times or the BBC, each with a unique following.
The topographical "maps" of these communities, generated by Pew using the data visualization tool NodeXL, aren’t just maps of relationships. They represent the channels of information in Twitter’s vast ecosystem, the roads and throughways, stoops and street corners in each topical neighborhood where users congregate and swap news and anecdotes.
“We’re not just looking at a social structure, but also the information that’s coursing around this circuit, this particular culture,” Rainie says. “You can see the information that has the most balance and who has the most influence. It complements the demographic snapshot we develop with public opinion data.”
But maps, of course, are tools for getting from one place to another, and the goal of this type of network analysis is to determine how the structure of communities shapes the spread of information across the social network’s millions of users. With 18 percent of American Internet users and 14 percent of the overall U.S. population on Twitter, understanding the geography of Twitter’s universe can help institutions and individuals understand how breaking news, gossip and misinformation propagate across the space.
For an institution with defined objectives like a political organization or a marketing firm, these maps of Twitter communities could be essential in helping to accomplish particular goals such as spreading a message, killing dissent or identifying potential allies and enemies in an online ecosystem where Americans are increasingly focusing their attention.
“If you’re a political actor, and if you manage to identify a certain social structure, it helps you figure out the way the world is working and what strategies are working,” Itai Himelboim, a professor at the University of Georgia who co-authored the report, told Al Jazeera. “But it also brings up questions about if you’re getting all the information you need to be a power broker. Are you missing out on alliances of constituencies? What’s the best place to spread your message, and who can you enlist to help you do this?”
Fil Menczer, a professor at the University of Indiana Bloomington School of Informatics and Computing, has researched the potential applications of this type of analysis for years. Menczer’s research touches on every aspect of Twitter’s role as a mirror for human communities, like examining the relationship between social data and the stock market, the spread of infectious diseases and how political campaigns manipulate data to spread misleading information. In a 2012 paper on the spread of memes on Twitter, Menczer and his team sought to demystify how information spreads on unrelated topics, yielding similar network structures to those uncovered by Pew.
"Imagine, for example, that you’re interested in knowing what type of people are discussing a similar topic, and you find a certain structure with a clear hub; that is, people are following this source and retweeting and retweeting,” Menczer told Al Jazeera. “If I want to be influential with this topic, I have to get to this person. Or, on the other hand, if I am trying to promote a question that is against a particular meme, I can say ‘Well, if I discredit this person, that network will crumble.’”
But having a million followers doesn’t necessarily mean you’ll succeed. If a community of highly influential people is especially dense — meaning each member has several connections to other members — the influential hubs of that community can act as an "amplifier and a trap." An potential example could be several journalists with triple-digit Twitter followings tweeting to each other about a newsletter they all read.
“Things go into this network but don't come back out,” said Menczer. “Messages that tend to go truly viral tend to be those that are not trapped by a dense number of communities. It’s those that cross boundaries.”
One of the major lessons of network analysis, both Pew and Menczer emphasize, is that the Twitter commons hasn’t necessarily made society as democratic as techno-utopians would have you believe. Twitter isn’t a wide-open space, free of boundaries or obstacles: It’s a "mirror," as Menczer says, for the social structures of the real world.
“One of the presumptions about the rise of social media is that it’s changed everything,” says Himelboim. “In fact, if you look at the broadcast networks and brand clusters (two archetypes described by Pew), big, important and powerful institutions that wield tremendous influence offline still do on the Internet. This is really a reality check against those louder voices who claim the world has somehow been transformed."
“It makes you wonder about polarization in political discourse: Is this something that social media is responsible for?” asks Menczer. “Is more polarization easier because of social media, or are we observing what was already there with new technology? Or, even simpler: Would our discourse be better if Twitter and Facebook just didn’t exist?”
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