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Accusations began to fire. Just who would want to try and throw people off the trail and confuse them, and who would have a new, large photo of her? Boxxy herself, or a close accomplice was the consensus. They must have caught wind of her full name being found, and merely be attempting to mitigate the damage by stirring the pot with false leads. 

It sounded semi-plausible, but, unbeknownst to the vast majority of /b/ at that moment, the CBRC had long since uncovered a photobucket account which was later seen to contain the same photos, so the implication is obvious, members of the CBRC were trolling /b/ with the photos in a attempt to throw them off, as they themselves were close to breaking into her accounts and did not want Anonymous to do it first.

We have no way of verifying if they were telling the truth, or if any of the claimed locations were in any way accurate but the mere possibility of this is shocking indeed. Thankfully, these were almost certainly fake - one of the addresses was a mall, one of the phone numbers was for a chiropractor.

TextAnalyst processes textual data through what is termed "natural language text analysis." Using linguistic rules and "artificial neural network technology," the program mimics human cognitive analytical processes. It begins by processing each document as a sequence of symbols, generating a hierarchical semantic network structure based on the frequency of terms and the relationships between them. After analyzing the document, each term (or theme) within the network is assigned an individual statistical weight (range 0-100) relative to its importance within the entire text. Additionally, the relationships between terms are also assigned a statistical weight, in effect highlighting the strength of thematic associations. TextAnalyst then engages in the process of renormalization - adjusting the statistical weight of each term based on its relationship to others. The renormalized values are termed "semantic weights" and can be arranged into a semantic network. High semantic weights are indicative of a term or theme having considerable significance within the overall text. Inter-item weights, also presented in the figures to follow, suggest significant association between text themes.

TextAnalyst processes textual data through what is termed "natural language text analysis." Using linguistic rules and "artificial neural network technology," the program mimics human cognitive analytical processes. It begins by processing each document as a sequence of symbols, generating a hierarchical semantic network structure based on the frequency of terms and the relationships between them. After analyzing the document, each term (or theme) within the network is assigned an individual statistical weight (range 0-100) relative to its importance within the entire text. Additionally, the relationships between terms are also assigned a statistical weight, in effect highlighting the strength of thematic associations. TextAnalyst then engages in the process of renormalization - adjusting the statistical weight of each term based on its relationship to others. The renormalized values are termed "semantic weights" and can be arranged into a semantic network. High semantic weights are indicative of a term or theme having considerable significance within the overall text. Inter-item weights, also presented in the figures to follow, suggest significant association between text themes.

In the case of the One Machine we should look for evidence of self-governance at the level of the greater cloud rather than at the component chip level. A very common cloud-level phenomenon is a DDoS attack. In a Distributed Denial of Service (DDoS) attack a vast hidden network of computers under the control of a master computer are awakened from their ordinary tasks and secretly assigned to "ping" (call) a particular target computer in mass in order to overwhelm it and take it offline. Some of these networks (called bot nets) may reach a million unsuspecting computers, so the effect of this distributed attack is quite substantial. From the individual level it is hard to detect the net, to pin down its command, and to stop it. DDoS attacks are so massive that they can disrupt traffic flows outside of the targeted routers - a consequence we might expect from an superorganism level event.

Unsurprisingly the vast flows of bits in the global internet exhibit periodic rhythms. Most of these are diurnal, and resemble a heartbeat. But perturbations of internet bit flows caused by massive traffic congestion can also be seen. Analysis of these "abnormal" events show great similarity to abnormal heart beats. They deviate from an "at rest" rhythms the same way that fluctuations of a diseased heart deviated from a healthy heart beat. Prediction: The One Machine has a low order of autonomy at present. If the superorganism hypothesis is correct in the next decade we should detect increased scale-invariant phenomenon, more cases of stabilizing feedback loops, and a more autonomous traffic management system.

3) Perhaps 4chan is its face? Perhaps Anonymous speaks for the ii? Memes drift up out of the morass of /b/tards into the world, seemingly without a concrete source. “I CAN HAZ CHEEZBURGER” may be the global intelligence saying “hi”… or perhaps more poetically, babbling like a baby. http://online.wsj.com/article/SB121564928060441097.html?mod=rss_E-Commerce/Media

Media literacy is the capacity to access, analyze, evaluate, and communicate messages in a wide variety of forms.

Like literacy in general, media literacy is applied in a wide variety of contexts—when watching television or reading newspapers, for example, or when posting commentary to a blog. Indeed, media literacy is implicated everywhere one encounters information and entertainment content.

The foundation of effective media analysis is the recognition that: • all media messages are constructed • each medium has different characteristics and strengths and a unique language of construction • media messages are produced for particular purposes • all media messages contain embedded values and points of view • people use their individual skills, beliefs, and experiences to construct their own meanings from media messages • media and media messages can influence beliefs, attitudes, values, behaviors, and the democratic process Making media and sharing it with listeners, readers, and viewers is essential to the development of critical thinking and communication skills. Feedback deepens reflection on one’s own editorial and creative choices and helps students grasp the power of communication.

When students woke up that September morning and saw News Feed, the first reaction, generally, was one of panic.

When the folks at Britannica conducted a forensic analysis of the failure, they learned something shocking: the site had crashed because, within its first hours, it had attracted nearly fifty million visitors.

Wikipedia was the modern birth of “crowdsourcing”, the idea that vast numbers of anonymous individuals can labor together (at a distance) on a common project.

There’s a new logic operating: the more something is shared, the more valuable it becomes.

Meier has found that an increase in cell-phone availability increases the likelihood (at least perceived by the public) that the government might be overthrown by violent means.

Meier has found that an increase in cell-phone availability increases the likelihood (at least perceived by the public) that the government might be overthrown by violent means.