carapace – Not your father's america

Microsoft Academic Search is a free academic search engine developed by Microsoft Research, which also serves as a test-bed for many research ideas in Data Mining, Named Entity Extraction and Disambiguation, Data Visualization, etc. As a research prototype, the coverage of MAS is still very limited in certain domains. Microsoft Academic Search provides many innovative ways to explore academic publications, authors, conferences, journals, organizations and keywords, connecting millions of scholars, students, librarians, and other users

New research has analysed the mood of Twitter users in the UK and detected various changes in the mood of the public. In particular, the researchers observed a significant increase in negative mood, anger
and fear, coinciding with the announcement of spending cuts and last summer’s riots together with a possibly calming effect during the royal wedding.

http://www.eurekalert.org/pub_releases/2012-04/uob-csm041612.php

April 05, 2012

Nicole Hemsoth

If we were all granted an hour-long crash course in data mining for every bit of information we’ve passed on about ourselves this week alone, something says that we’d be seasoned experts by now.

There seems to be growing awareness about the pervasiveness of data mining with a rash of recent news items and profile pieces covering the topic.

Arguably, the case of the pregnant teen that was ratted out by Target’s data mining oracle brought it to light first, but just the other afternoon the topic was front and center on popular talk programs, including NPR’s Diane Ream Show.

What many of these conversations overlooked was the actual process behind the data wrangling. In fact, some might say that the popular media has started “demonizing” the term “data mining”—associating it with covert corporate prying or at its worst, government espionage on its own citizenry.

This week, the long-standing, general interest magazine, The Atlantic, seemed to address this issue by publishing a rather detailed article that describes data mining as a concept, science and practice—and informed the masses why this is one technology they should fully understand in this world of sensors, signals and connectivity.

Without sentimentalizing in either direction on the topic, Alexander Furnas, a master’s candidate at the Oxford Internet Institute and author of the data mining cheat sheet, removes the judgment and explores what data mining is, isn’t, and what it might be in the future.

Even though it seems to many outside of tech circles that data involves some kind of strange arcane magic, “the functioning of data mining algorithms is quite complex….[but] the users and capabilities of these approaches are, in fact, quite comprehensible and intuitive.”

“For the most part, data mining tells us about very large and complex data sets, the kinds of information that would be readily apparent about small and simple things. For example, it can tell us that "one of these things is not like the other" a la Sesame Street or it can show us categories and then sort things into pre-determined categories. But what’s simple with 5 datapoints is not so simple with 5 billion datapoints.”

In his condensed “everything you need to know” article, he manages to provide succinct definitions that put the core concepts of pattern recognition in context. He offers definitions of anomaly detection, association learning, cluster detection, classification and regression—using examples from businesses and common practices, including Amazon’s recommendation engine and spam filters for email clients.

He says that the tools and techniques of data mining are increasing in sophistication, not just because of the natural course of discovery and new approaches to data mining come to light, but also because there are so many data sources with so much subtlety, the tools behind the new wave of “big data” are essential.

As he writes, “At these scales patterns are often too subtle and relationships too complex or multi-dimensional to observe by simply looking at the data. Data mining is a means of automating part this process to detect interpretable patterns; it helps us see the forest without getting lost in the trees.”

We give kudos to Furnas for writing an overview guide to a complex topic for a general audience and using a Sesame Street reference without sounding patronizing. As he writes—right to the very heart of where the big data problem fits in—the world of data mining is becoming more complex as more data becomes available and the tools to manage it are overextended.

This is critical information for ordinary citizens since understanding how far even a little data can go can help people make smarter decisions about how their share and protect their information.

The problem is, while it’s nearly impossible to live off the grid and outside of the purview of data mining from governments and companies alike, too few people understand what goes on behind the scenes of both of these entities with information we’ve unwittingly or unthinkingly given

From: Datanami Weekly Update

Legislation to make it illegal to use “offensive” language online

Steve Watson
Infowars.com
April 2, 2012

The state legislature of Arizona has passed a bill that vastly broadens telephone harassment laws and applies them to the Internet and other means of electronic communication.

The law, which is being pushed under the guise of an anti-bullying campaign, would mean that anything communicated or published online that was deemed to be “offensive” by the state, including editorials, illustrations, and even satire could be criminally punished.

The Comic Book Legal Defense Fund breaks down Arizona House Bill 2549:

“The bill is sweepingly broad, and would make it a crime to communicate via electronic means speech that is intended to ‘annoy,’ ‘offend,’ ‘harass’ or ‘terrify,’ as well as certain sexual speech. Because the bill is not limited to one-to-one communications, H.B. 2549 would apply to the Internet as a whole, thus criminalizing all manner of writing, cartoons, and other protected material the state finds offensive or annoying.”

First Amendment activist group Media Coalition has written to Arizona Governor Jan Brewer, urging her not to sign the legislation into law.

The letter notes that the terms used in the bill are not defined in the statute or by reference, and thereby the law could be broadly applied to almost any statement.

• “H.B. 2549 would make it a crime to use any electronic or digital device to communicate using obscene, lewd or profane language or to suggest a lewd or lascivious act if done with intent to ‘annoy,’ ‘offend,’ ‘harass’ or ‘terrify,’” the letter notes. … ‘Lewd’ and ‘profane’ are not defined in the statute or by reference. ‘Lewd’ is generally understood to mean lusty or sexual in nature and ‘profane’ is generally defined as disrespectful or irreverent about religion or religious practices.”

“H.B. 2549 is not limited to a one to one conversation between two specific people. The communication does not need to be repetitive or even unwanted. There is no requirement that the recipient or subject of the speech actually feel offended, annoyed or scared. Nor does the legislation make clear that the communication must be intended to offend or annoy the reader, the subject or even any specific person.” the letter continues.

In this respect the law could even technically be applied to someone posting a status update on Facebook.

“Speech protected by the First Amendment is often intended to offend, annoy or scare but could be prosecuted under this law.”The Media Coalition letter continues.

“A Danish newspaper posted pictures of Muhammad that were intended to be offensive to make a point about religious tolerance. If a Muslim in Arizona considers the images profane and is offended, the paper could be prosecuted. Some Arizona residents may consider Rush Limbaugh’s recent comments about a Georgetown law student lewd. He could be prosecuted if he intended his comments to be offensive. Similarly, much general content available in the media uses racy or profane language and is intended to offend, annoy or even terrify.”

“Bill Maher’s stand up routines and Jon Stewart’s nightly comedy program, Ann Coulter’s books criticizing liberals and Christopher Hitchens’ expressions of his disdain for religion, Stephen King’s novels or the Halloween films all could be subject to this legislation. Even common taunting about sports between rival fans done online is frequently meant to offend or annoy, and is often done using salty and profane language.”

This type of legislation is far from unprecedented. Last year, former president Bill Clinton proposed a law to censor internet speech. “It would be a legitimate thing to do,” Clinton said in an interview that aired on CNBC. Clinton suggested the government should set-up an agency that monitors all media speech for supposed factual errors.

“That is, it would be like, I don’t know, National Public Radio or BBC or something like that, except it would have to be really independent and they would not express opinions, and their mandate would be narrowly confined to identifying relevant factual errors” he said. “And also, they would also have to have citations so that they could be checked in case they made a mistake. Somebody needs to be doing it, and maybe it’s a worthy expenditure of taxpayer money.”

Cass Sunstein, head the Office of Information and Regulatory Affairs, has also proposed banning speech on the internet that the government disagrees with. Sunstein proposed the creation of an internet “Fairness Doctrine” similar to the one that was used for years to limit and eliminate free speech on the radio.

This legislation represents yet another move to police and control freedom of expression via the internet. Once again it grants the state and the government the direct right to determine what is and is not “offensive” on a whim. It then allows for the prosecution of individuals and organisations based on such summations – an extremely dangerous precedent to set.

Steve Watson is the London based writer and editor for Alex Jones’ Infowars.net, and Prisonplanet.com. He has a Masters Degree in International Relations from the School of Politics at The University of Nottingham in England.

19 Mar 2012

A University of California, Riverside professor and several other researchers have developed a model that uses data from Twitter to help predict the traded volume and value of a stock the following day.

Read at: http://ucrtoday.ucr.edu/4158

FBI Fact Sheet on Internet Fraud: Includes information on: Avoiding Internet Auction Fraud, Avoiding Non-Delivery of Merchandise, Avoiding Credit Card Fraud, Avoiding Investment Fraud, Avoiding Business Fraud, Avoiding the Nigerian Letter or “419” Fraud, Common Fraud Scams, Investment-Related Scams, Internet Scams, and Fraud Target: Senior Citizens.