CS115/MAS115: Computing for The Socio-Techno Web image source: http://www.igenii.com/blog/Social%20Media/social-media/ twitter.com http://www.worthofweb.com/blog/case-study-this-revolution-will-be-tweeted/ http://foxwoodonlinemarketing.typepad.com/my-blog/social-media/ CS115/MAS115: Computing for The Socio-Techno Web Digital Footprints

BITS and BYTES Discuss: How many patterns can be represented with 2 bits? How about 3 bits? How about a byte? http://simplyted.blogspot.com/2005/12/how-to-visualize-data.html A bit stores just a 0 or 1 Group 8 bit to make a byte Kilobyte, KB, about 1 thousand bytes Megabyte, MB, about 1 million bytes Gigabyte, GB, about 1 billion bytes Terabyte, TB, about 1 trillion bytes

Koan 1: Everything is bits

Koan 2: Perfect copy, every time

Koan 3: There is want in the midst of plenty

Koan 4: Processing is power

MooRe’s Law

What if “exponential growth” continues? Inventor and Futurist Ray Kurtzweil predicts that we will be creating computers smarter than a human by 2029; smarter than all humans by 2060.

Koan 5: More of the same can be different Image source: http://blog.tinydeal.com/2013/01/16/how-to-choose-a-good-camera/

More of the same can be different Lots of laws (about public records, for example), were based in the assumption that it was difficult for a human to derive too many results from public records. Public records were created for checking. Not for predicting. KOAN 5: More of the same… Just because something was allowed, it does not mean it was accessible. Adding accessibility to big collections of info is a game changer. http://fundrace.huffingtonpost.com/neighbors.php?type=name&lname=Clinton&fname=Hilary&search=Search

Koan 6: Cyberworld’s everlasting memory Can you find an online instance of this?

Koan 7: Speed of (mis?)information KOAN 7: Bits move faster than thought. How do you know what to believe? Refer to paper with Graham. Late Thursday, a Twitter account with the handle @BBCNewsUKI sent out a message claiming Buckingham Palace had announced the death of Queen Elizabeth II, the reigning monarch of the United Kingdom. “Circumstances are unknown,” the tweet read. “More details to follow.” The news had an air of believability: Elizabeth is 90 years old and has been in poor health recently. This year, for the first time in three decades, she failed to attend a Christmas Day church service near her country home in Norfolk after suffering what was described as a “heavy cold.” The queen has not appeared in public since she fell ill. Additionally, if the queen were to pass away, it is the BBC that would make the announcement.  The tweet, of course, was not real. @BBCNewsUKI followed up its tweet with the rather less-BBC-like message, “Love a Tuesday off if the queens dead, announce it before it's too late.” The account was a fairly obvious fake, and it was soon suspended by Twitter. But rumors that the queen was dead still sparked a frenzy online, with users rushing to add condolences and others attempting to verify the news. A number of Twitter users began tweeting that there had been a “media blackout” in an attempt to hide news of the queen's death from the public. By Friday, it was one of the top trending topics on Twitter — though many of the tweets appeared to be mocking the idea. How does mis information spread is a source of discussion and research – we will get back to that later in the semester. Misinformation of a different kind occurred in the United States during the December 2012 Newtown shootings and the April 2013 Boston bombings. In the Newtown case, online and mainstream media misidentified a Facebook page as that of the shooter. After the Boston bombings, social media users engaged in online detective work, examining images taken at the scene and wrongfully claiming that a missing student was one of the bombers. But in this case, mainstream media outlets also played a part in perpetuating and validating the misinformation by publishing images of the wrong suspects. How can we understand such large volumes of data that move so quickly? Any online information is part of a larger and more complex ecology, with many interconnected factors. It’s therefore very difficult to fully map the processes involved in the rapid spread of misinformation or to identify where this information originates. Discuss: can you find other examples?