Sonia Livingstone on Children and the Internet

Sonia Livingstone on Children and the Internet on Social Science Bites (SAGE)

Nigel Warburton – You mentioned exposure to pornography, to racism, to cyber-bullying, is that the limit of risk for a child online?

Sonia Livingstone – Among the most common risks are exposure to pornography and cyber-bullying, though those remain relatively low level. The other risk that people really worry about, it the risk that strangers, paedophiles, ‘weirdos’ (as kids call them) will locate a child, especially a vulnerable child and will exploit and abuse them. And we spent quite a while thinking about firstly how to ask children about that, if they are not aware of those risks, because there are ethical issues in the research we are doing. And then, how to decide what is a risk, because many children go online precisely to meet new people and make new friends. And a ‘new friend’ before you get to know them is a stranger. So, working out which are the strangers who are going to become good friends and which are the ones who are going to harm you is a really subtle judgment that we are asking a child to make. Many children do the kinds of things that allow them to make new friends, like they post their personal information, and they add contacts to their social networking or their instant messaging that they don’t otherwise know, they put out all kinds of information about themselves. But, mainly, they don’t meet strangers and they certainly don’t meet weird strangers out to sexually abuse them.

Twitter will gauge voter sentiment in new venture

Twitter will gauge voter sentiment in new venture - NextGov

Image: The Guardian

“The initial installment of the Twitter Political Index, called the “TwIndex” for short, shows Obama with a score of 34 and Romney with 25, based on tweets posted on Tuesday. Since the TwIndex compares tweets about the candidates to all tweets on other topics, that means that tweets about Obama are on average more positive than 34 percent of tweets not mentioning him. It also means that tweets about Obama are generally more positive than tweets about Romney. The plan is for the latest Twitter Political Index will be posted each day at 8 p.m. at election.twitter.com.” (NextGov.com)

How We Talk About Media Refusal, Part 1: “Addiction”

How We Talk About Media Refusal, Part 1: “Addiction” - FLOW

Image: Phillip Toledano, The Atlantic

“Practices of media refusal, as well as statements by media refusers about their choices, could be seen as implicit indictments of the norms of media culture, the most basic norm being that everyone ought to be a consumer of media. Yet media refusal is usually understood and practiced individually (though there have been a few campaigns aimed at getting people to collectively) unplug. This individual response to a collective problem is typical of contemporary “lifestyle politics” in which resistance tactics are arguably more effective at generating further consumption (of self-help magazines, for example) than actually altering objectionable aspects of consumer culture.” (Laura Portwood-Stacer, FLOW)

Bots Raise Their Heads Again on Facebook

Bots Raise Their Heads Again on Facebook - New York Times

Photo: Kimihiro Hoshino/Agence France-Presse — Getty Images

“The company, called Limited Run, helps bands and record labels sell music and merchandise online. It bought advertisements for itself on Facebook this spring. It wanted to know who was clicking, so it built its own analytics tool. It discovered that only one in five clicks seemed to be from human beings. The rest, it said, came from bots, which, in essence, are bits of software performing automated tasks.” (Somini Sengupta, NYTimes.com Bits)

The Problem with Crowdsourcing Crime Reporting

“Crowdsourcing is not entirely flawed in the Mexican context, though. We have seen people in various Mexican cities organize organically to alert one another of violent events, in real time. But these urban crisis management networks do not need institutions to function. However, law enforcement does, unless one is willing to accept lynching and other types of crowd-based law enforcement.” (Andrés Monroy-Hernández, Social Media Collective)

Carnegie Mellon Performs First Large-Scale Analysis of “Soft” Censorship of Social Media in China

Carnegie Mellon Performs First Large-Scale Analysis of "Soft" Censorship of Social Media in China - Carnegie Mellon News

Image: Carnegie Mellon

“Researchers in Carnegie Mellon University’s School of Computer Science analyzed millions of Chinese microblogs, or ‘weibos,’ to uncover a set of politically sensitive terms that draw the attention of Chinese censors. Individual messages containing the terms were often deleted at rates that could vary based on current events or geography.

In China, where online censorship is highly developed, the researchers found that oft-censored terms included well-known hot buttons, such as Falun Gong, a spiritual movement banned by the Chinese government, and human rights activists Ai Weiwei and Liu Xiaobo. Others varied based on events; Lianghui, a term that normally refers to a joint meeting of China’s parliament and its political advisory body, became subject to censorship when it emerged as a code word for “planned protest” during pro-democracy unrest that began in February 2011.” (Byron Spice, Carnegie Mellon News)

How to Predict the Spread of News on Twitter

How to Predict the Spread of News on Twitter - Technology Review

Graphic: Technology Review

“Here’s their conclusion: ‘Our experiments show that it is possible to estimate ranges of popularity with an overall accuracy of 84% considering only content features.’

That’s pretty impressive and may herald important changes in the way articles are written and edited. It’s not hard to imagine an automated article checker—rather like the grammar checkers in word processing programs–that reads articles and predicts how popular they are likely to be when published.

In a sense, that’s what journalists do now when they choose topics to write about. But this process is entirely intuitive, based as much on gut feel as on a good understanding of the dynamics of the audience. Huberman’s algorithm could automate this process.” (KFC, Technology Reivew)