The racial inequalities afflicting Americans and our society today are in many ways a result of the result of spatial segregation.

White people and nonwhite people tend to live in different neighborhoods, go to different schools and have dramatically different economic opportunities based on their race.

That physical manifestation of structural racism has been true historically in this country, and is still the case today.

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A researcher from New York University demonstrated that websites focusing on racial issues are visited less often, and are less visible in search result rankings than sites with different, or broader, focuse

WHAT MAKES A 'RACIAL' SITE? Researchers relied on website metatags – website producers' descriptions of the site coded to be picked up by and reflected in search engine results. Mcilwain designated as 'racial' websites with metatags including terms such as 'african american,' 'racism,' 'hispanic,' 'model minority' and 'afro.' Sites without those terms in their metatags he designated 'nonracial.' Advertisement

Today's internet is built on a similar spatial logic.

People travel from website to website in search of content in the same way they travel from neighborhood to neighborhood looking for stuff to do and people to hang out with.

Websites accrue and compound value as visitor traffic and site visibility increases.

But there is a crucial difference: Internet users have – more or less – complete freedom to travel where they choose.

Websites can't see the color of a user's skin and police incoming traffic in the same way human beings can and do in geographical spaces.

Therefore, it's easy to imagine that the internet's very structure – the social environments it produces and the new economies it births – might not be racially segregated the way the physical world is.

And yet the internet does appear in fact segregated along racial lines.

My research demonstrates that websites focusing on racial issues are visited less often, and are less visible in search result rankings than sites with different, or broader, focuses.

THE TOP 10 'RACIAL' WEBSITES For the study, researchers analyzed what Alexa.com characterizes as the internet's top 56 African-American sites using a software program called Voson. Voson crawls the web to identify what websites the source sites link to, and what sites link to the source sites. The nonracial websites show below are the top 10 sites on the web, which were also characterized by Alexa.com. RACIAL WEBSITES Bet.com Vibe.com Essence.com Okayplayer.com Blackplanet.com Thesource.com Blackamericaweb.com Ebony.com Blackenterprise.com Eurweb.com NONRACIAL WEBSITES Google.com Youtube.com Facebook.com Baidu.com Wikipedia.org Yahoo.com Google.co.in Qq.com Reddit.com Taobao.com To make this type of distinction between websites, the researcher, Charlton Mcilwain, relied on website metatags – website producers' descriptions of the site coded to be picked up by and reflected in search engine results. Mcilwain designated as 'racial' websites with metatags including terms such as 'african american,' 'racism,' 'hispanic,' 'model minority' and 'afro.' Sites without those terms in their metatags he designated 'nonracial.' By using website metatags, Mcilwain was able to distinguish between racial and nonracial sites (and the segregated traffic between them) based on whether the site's producers themselves define the site's identity in racial terms. Advertisement

This phenomenon is not based on anything that individual website producers do.

Rather, it appears to be a product of how users themselves find and share information online, a process mediated mostly by search engines and, increasingly, social media platforms.

Words like 'racist' and 'racism' are loaded terms, primarily because people almost always associate them with individualized moral and cognitive failures.

In recent years, though, the American public has become increasingly aware that racism can apply to cultures and societies at large.

My work looks for online analogues of this systemic racism, in which subtle biases permeate society and culture in ways that yield overwhelming advantages for whites, at the expense of nonwhites.

WHAT THE RESEARCHERS FOUND A researcher from New York University demonstrated that websites focusing on racial issues are visited less often, and are less visible in search result rankings than sites with different, or broader, focuses. Significantly greater numbers of clicks between nonracial sites, and fewer numbers of clicks between racial and nonracial sites were found. That indicates that users are going out of their way to visit nonracial sites. The data also showed that nonracial sites rank significantly higher in search results, and therefore likely enjoy greater visibility, than racial sites. Significantly greater numbers of clicks between nonracial sites, and fewer numbers of clicks between racial and nonracial sites were found. That indicates that users are going out of their way to visit nonracial sites The racial sites are less visible, get less traffic and therefore likely reap fewer benefits from visibility (such as advertising revenue or higher search engine rankings). It's likely that people type a word or phrase into a search engine like Google. In fact, direct traffic accounts for only about one-third of the traffic flow to the web's top sites. Advertisement

Specifically, I am trying to determine whether the online environment, one completely constructed by humans, systematically produces advantages and disadvantages along racial lines – whether intentionally or inadvertently.

This is a difficult question to approach, but I begin by assuming that today's technological systems have developed within a culture and society that is systemically and structurally racist.

This makes it possible – even likely – that existing biases operate in similar ways online.

In addition, the historical geographical configurations that produced and perpetuated racial inequality provide a useful guide to investigating what systemic racism might look like online.

The online landscape, and how people travel through it, are both important factors to understand this picture.

First, I wanted to look at the map – how the web itself is structured by website producers.

I analyzed what Alexa.com characterizes as the internet's top 56 African-American sites using a software program called Voson.

IS GOOGLE AUTOCOMPLETE RACIST? A study from 2013 by a top university had claimed internet giant Google’s search facility 'perpetuates prejudices'. The investigation from Lancaster University found that results from Google’s auto-complete internet search tool produce suggested terms which could be viewed as racist, sexist or homophobic. The study by a team at Lancaster University’s Faculty of Arts and Social Sciences comes as a German federal court has told Google to clean up the results its search engine suggests. The court had said Google must ensure terms generated by auto-complete, which represent the level of questions people are asking, are not offensive or defamatory. The FASS study found some shocking results in its UK study, which drew out more than 2,600 questions on the Google search tool and categorized the answers. And it warns that 'humans may have already shaped the internet in their image, having taught stereotypes to search engines.' The research revealed high proportions of negative evaluative questions for black people, gay people and males. For black people, these questions involved constructions of them as lazy, criminal, cheating, under-achieving and suffering from various conditions such as dry skin or fibroids. Gay people were negatively constructed as contracting AIDS, going to hell, not deserving equal rights, having high voices or talking like girls. The negative questions for males positioned them as catching thrush, under-achieving and treating females poorly. A Google spokesperson said the system was entirely automated. Advertisement

Voson crawls the web to identify what websites the source sites link to, and what sites link to the source sites.

Then I set out to determine the racial content, if any, of each of those thousands of websites, to begin measuring any inequalities that might exist in the online landscape.

Measuring spatial inequality offline typically involves measuring attributes of the people who live in a specific geographic location.

For example, ZIP code 65035 designates a 'white' neighborhood because 99.5 percent of the people residing there (Freeburg, Missouri) are white, according to U.S. census data.

By contrast, ZIP code 60619, an area in Chicago, would be considered 'nonwhite,' because 0.7 percent of its residents are white.

To make this type of distinction between websites, I relied on website metatags – website producers' descriptions of the site coded to be picked up by and reflected in search engine results.

I designated as 'racial' websites with metatags including terms such as 'african american,' 'racism,' 'hispanic,' 'model minority' and 'afro.' Sites without those terms in their metatags I designated 'nonracial.'

By using website metatags, I was able to distinguish between racial and nonracial sites (and the segregated traffic between them) based on whether the site's producers themselves define the site's identity in racial terms.

Once I had labeled each site as racial or nonracial, I looked at the links website producers created between them.

There were three possible types of links: between two racial sites, between two nonracial sites, or between a racial site and a nonracial one.

How many of each type of link the data contained would reveal whether bias influenced website producers' decisions.

If there were no bias, the number of links would be proportional to the number of each type of site in the data set. If there were bias, the numbers of links would be disproportionately high or low.

While I found slight differences between the ideal theoretical proportions and the actual number of links, they were not significant enough to indicate that any segregation in people's internet behavior is caused by web producers.

People who travel the web just clicking links on websites at random would not arrive at racial or nonracial sites substantially more or less than they should based on the number of such sites that exist.

But people don't just follow links; they exercise their preferences when navigating the web.

For my second inquiry, I wanted to find out how people actually move between websites.

The data also showed that nonracial sites rank significantly higher in search results, and therefore likely enjoy greater visibility, than racial sites. The racial sites are less visible, get less traffic and therefore likely reap fewer benefits from visibility

I looked at the same 56 sites as for the previous analysis, but this time used Similarweb, a prominent web traffic metrics site.

For each site, Similarweb produces data showing what websites people came from and what websites people navigated to next.

I characterized those sites, too, as 'racial' or 'nonracial,' and identified three types of paths people took when clicking: between two racial sites, between two nonracial sites, or between a racial site and a nonracial one.0

In this analysis, the number of clicks between different types of sites would reveal whether bias influenced users' decisions.

I found significantly greater numbers of clicks between nonracial sites, and fewer numbers of clicks between racial and nonracial sites.

That indicates that users are going out of their way to visit nonracial sites.

This gets us closer to the whole story when it comes to segregated traffic patterns and potential inequalities along racial lines.

My data also showed that nonracial sites rank significantly higher in search results, and therefore likely enjoy greater visibility, than racial sites.

The racial sites are less visible, get less traffic and therefore likely reap fewer benefits from visibility (such as advertising revenue or higher search engine rankings).

ONLINE SHOPPING CAN REVEAL IF YOU ARE RACIST Shoppers are more likely to buy a product advertised from an online classified advert if they think the seller is white, a new study suggests. A year-long experiment examining the sales of iPods on Craigslist in the U.S. revealed racial bias as black sellers did worse than their white counterparts The research showed that black sellers got fewer responses and lower offers for their iPods, while shoppers were also less attracted to white sellers with tattoos on their wrists. U.S. researchers posted 1,200 classified adverts in over 300 areas of the U.S. between March 2009 and March 2010, to test for racial bias among buyers by featuring similar photos of the iPod held by a man’s hand that was wither black, white or white with a wrist tattoo. The experiment found black sellers receive 13 percent fewer responses, 18 percent fewer offers and the money offered was 12 percent lower than that offered to a white seller. White sellers with wrist tattoos were found to have similar responses and offers. In the study, published in the Economic Journal of the Royal Economic Society, buyers interacting with black sellers behaved in ways that suggested they trusted them less. They were 17 percent less likely to include their names, 44 per cent likely to agree to a proposed delivery by mail and 56 per cent more likely to express concern about making a long distance payment. Advertisement

It might be tempting to suggest that this merely reflects user preferences.

That could be true if users knew what websites they want to go to, and then navigate directly to them.

But usually, users don't.

It's much more likely that people type a word or phrase into a search engine like Google.

In fact, direct traffic accounts for only about one-third of the traffic flow to the web's top sites.

To quote a conclusion from search optimization firm Brightedge, 'overwhelmingly, organic search trumps other traffic generators.'

While more research is of course necessary, my work so far suggests that in conjunction with users' preferred choices to navigate to nonracial sites more than racial sites, search engines do something with a similar effect: Nonracial sites rank significantly higher than racial sites.

That can give racial sites less traffic and less financial support in the form of advertising revenue.

In both of these situations, people and search engines steer traffic in ways that give advantages to nonracial websites and disadvantages to racial sites.

This approximates what, in the offline world, is called systemic, structural racism.