[OPLIN 4cast] OPLIN 4cast #389: Shared sentiments

Wed Jun 11 10:30:12 EDT 2014

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OPLIN 4Cast

OPLIN 4cast #389: Shared sentiments
June 11th, 2014

sarcasm alert signLast week, Nextgov reported 
<http://www.nextgov.com/defense/2014/06/secret-service-software-will-detect-sarcasm-social-media-users/85633/> 
that the Secret Service has released a request for software to analyze 
social media data with one of the requested capabilities being the 
"ability to detect sarcasm." The reason for the sarcasm request is an 
attempt to avoid a computer-triggered, aggressive law enforcement 
reaction to a social media post expressing malicious intent, only to 
find that the post was sarcastic - but of course, the request unleashed 
a whole flurry of snarky articles on the interwebs. Actually, though, 
businesses worldwide have been intensely interested in such an 
improvement to "sentiment analysis" of social media for years. A bad 
opinion posted and repeated in social media can do a lot of damage to 
any organization if the organization is slow to react, but what if a 
"good" opinion is actually sarcasm?

  * Sarcasm-detecting software doesn't exist, would be helpful
    <http://nymag.com/scienceofus/2014/06/computers-are-still-terrible-at-getting-sarcasm.html>
    (nymag.com/Jesse Singal) "The problem is that this is a very tough
    thing for computers to do - partly because it's a very tough thing
    for humans to do. In regular speech, humans can rely on subtle cues
    that someone is being sarcastic.... These cues obviously aren't
    present in text, which explains why jokes often don't translate over
    SMS or Twitter. So it's no surprise that computer scientists haven't
    yet been all that successful in training software programs to
    recognize sarcasm."
  * US Secret Service wants software to "detect sarcasm" on social media
    <http://arstechnica.com/tech-policy/2014/06/us-secret-service-wants-software-to-detect-sarcasm-on-social-media/>
    (Ars Technica/Joe Silver) "Sarcasm analysis in the realm of politics
    'requires some background knowledge, which computers are not good
    at,' [computer scientist and author Bing Liu] said. Others argue
    that the work order shows the intelligence community's fundamental
    lack of understanding of how the Internet works. For example, The
    Consumerist
    <http://consumerist.com/2014/06/04/you-could-be-the-person-who-builds-sarcasm-detection-software-for-the-secret-service-no-really/>'s
    Mary Beth Quirk said, 'Basically, the Secret Services would love it
    if someone would explain the Internet so it doesn't go around
    arresting sarcastic people with itchy social media trigger fingers.'"
  * Even Secret Service computers don't get sarcasm
    <http://www.bloombergview.com/articles/2014-06-06/even-secret-service-computers-don-t-get-sarcasm>
    (BloombergView/Leonid Bershidsky) "Though developers would have us
    think their linguistic tools are quite advanced, they should not be
    trusted to perform anything but the most rudimentary tasks. The
    generally accepted level of accuracy for sentiment analysis - a
    branch of computer linguistics that determines the positive or
    negative slant of a piece of text - is about 65 percent, though some
    developers claim higher rates
    <http://blog.mashape.com/post/48757031167/list-of-20-sentiment-analysis-apis>."
  * Stanford algorithm analyzes sentence sentiment, advances machine
    learning
    <http://engineering.stanford.edu/news/stanford-algorithm-analyzes-sentence-sentiment-advances-machine-learning>
    (Stanford University Enginnering/Tom Abate) "As we increasingly
    share these opinions via social networks, one result is the creation
    of vast reservoirs of sentiment that could, if systematically
    analyzed, provide clues about our collective likes and dislikes with
    regard to products, personalities and issues. Against this backdrop,
    Stanford computer scientists have created a software system that
    analyzes sentences from movie reviews and gauges the sentiments they
    express on a five-point scale from strong like to strong dislike.
    The program, dubbed NaSent - short for Neural Analysis of Sentiment
    - is a new development in a field of computer science known as 'Deep
    Learning' that aims to give computers the ability to acquire new
    understandings in a more human-like way."

*/Articles via Ohio Web Library <http://ohioweblibrary.org>:/*

  * Mine your language
    <http://web.b.ebscohost.com.proxy.oplin.org/ehost/detail?sid=8f8ee0da-1a80-4f6d-bae5-e47daa6cf0ee%40sessionmgr115&vid=1&hid=118&bdata=JnNpdGU9ZWhvc3QtbGl2ZQ%3d%3d#db=sch&AN=83051944>.
    (/New Scientist/, 11/3/2012, p19/Douglas Heaven)
  * So So Dataied
    <http://web.a.ebscohost.com.proxy.oplin.org/pov/detail?sid=61cc74b4-162c-4c76-9907-86f7ae026d78%40sessionmgr4001&vid=1&hid=4214&bdata=JnNpdGU9cG92LWxpdmU%3d#db=pwh&AN=86240282>.
    (/New Republic/, 4/8/2013, p63/Leon Wieseltier)
  * Techniques and Applications for Sentiment Analysis
    <http://web.a.ebscohost.com.proxy.oplin.org/ehost/detail?sid=43743154-364f-4883-a996-e1f8e9e1e7c9%40sessionmgr4002&vid=1&hid=4214&bdata=JnNpdGU9ZWhvc3QtbGl2ZQ%3d%3d#db=buh&AN=87497844>.
    (/Communications of the ACM/, April 2013, p82-89/Ronen Feldman)

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