Tweets Like Us
New research Â into what our Google queries and tweets say about us in cyberspace shows that we're a pretty divided lot online.
What's new, though, is that we can now tell, just from visualizing the knowledge we seek on Google and the hashtags we frequent on Twitter, what unites us -- and what it is about the echo-chambers of today's identity politics that keeps us all arguing so much to begin with. Skeptical? Let's have a look.
Near to your browser? Go to Google Suggest and click on "Web search." Type in the word, "why." Thanks to an "auto-suggest" feature that this (and many other) search engines now use, just typing in the word "why" produces a list of suggested, presumably popular completions. Today's list? "Why did I get married?" is the most popular question, followed by "Why is the sky blue?" and "Why do dogs eat grass?"
Humorous? Yes, and according to a new data visualization tool called Web Seer from Flowing Media, a startup cofounded by ex-IBMers Fernanda Viegas and Martin Wattenberg, searches like these also give the Web-curious "a little peek into our collective souls," says Viegas. "Exploring this Web Oracle can be quite revealing of society's fears, curiosities and prejudices."
Ah, but we're just getting started. Let's now type in the question: "Why doesn't he...?" The results I got were: Â "call me" and "like me" and "ask me out." And sure enough, typing in the question, "Why doesn't she...?" gets you similar completions. The differences, though, are the most telling. Men tended to complete with "call me back?" and "just leave?" and "like me anymore?" while women appeared to be more interested in why he didn't "text back" and "want a relationship."
Viegas says deeper gender divisions start to surface when it comes to family issues. If you type in the question, "Is my daughter...?" you're most apt to get "pregnant" or "a virgin" or "gifted" or "austistic." If you type in the question, "Is my son...?" you're most likely to get "gay" or "on drugs." Says Wattenberg: "If you play around with this for a while, you start to see a portrait of people's anxieties and I think, ultimately, a very clear gender division in society."
When applied to politics, the exercise becomes even more interesting. "Are Republicans...richer than Democrats?" and "evil?" and are Democrats "socialist?" and "communists?" According to a Web Seer analysis, people asking political questions seem to be very confused about party differences. But again, what they appeared to agree upon was even more revealing. A Web Seer analysis shows that people Googling in this way agree that both Republicans and Democrats are "retarded" and "morons" and "destroying America" -- in other words, most of the people who query "Google Suggest" about U.S. politics are similarly, deeply skeptical about the effectiveness and the integrity of either party.
But that's just for starters. Consider Twitter. Viegas and Wattenberg did an analysis of Twitter trending topics over the 2010 Memorial Day weekend; hashtags during that time period included a range, from #wordsbeforedeath to #oilspill. The pair analyzed whether trending topics differed by race. After analyzing the photographs of those tweeting in those tagged conversations, Viegas and Wattenberg said they discovered that blacks and whites were mostly equally involved in some conversations but not others. In this case, whites and blacks were about equally involved in a conversation about #wordsbeforedeath -- but overwhelmingly segregated on the conversations having to do with #cookout and #oilspill.
"Cookout hashtag tweets were overwhelmingly being written by black authors and #oilspill tweets were overwhelmingly being written by white authors," said Viegas. The point here? Â "It's not to think, wow, there's racial segregation on the Web," Viegas said. "We sort of knew that; the Web is a reflection of real life. The point here is that this level of segregation is just one click away from the Twitter home page and it's happening in the trending topics. The fact that you can look at trending topics and be immersed in conversations that are so separate from one another is something to keep in mind."
Beyond simply insightful, these kinds of real-time "focus group" data visualizations are starting to be used by political groups, as well as by nonprofit causes seeking new supporters and social enterprises in search of some target markets or potential trouble spots beyond those which may seem obvious.
Got any insights of your own to share? Let us hear from you.