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<p><!-- Make sure you modify the 4Cast title in this section -->
<span style="font-size: 20px; font-weight: bold;
color: rgb(0, 0, 0); font-family: arial;
line-height: 110%;">OPLIN 4cast #389: Shared
sentiments</span><br>
<!-- Make sure you modify the date of the 4Cast in this section -->
<span style="font-size: 11px; font-weight: normal;
color: rgb(102, 102, 102); font-style: italic;
font-family: arial;">June 11th, 2014</span></p>
<!-- Begin copy of Web Source here -->
<p style="text-align: justify;font-size: 16px;
font-family: arial; line-height: 110%;"><img
src="cid:part4.02000703.01080309@oplin.org"
alt="sarcasm alert sign" align="left"
height="105" width="110">Last week, Nextgov <a
href="http://www.nextgov.com/defense/2014/06/secret-service-software-will-detect-sarcasm-social-media-users/85633/">reported</a>
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?
</p>
<div> </div>
<ul style="text-align: left;">
<li style="text-align: justify; font-size: 16px;
font-family: arial; line-height: 110%;"><a
href="http://nymag.com/scienceofus/2014/06/computers-are-still-terrible-at-getting-sarcasm.html">Sarcasm-detecting
software doesn't exist, would be helpful</a>
(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."</li>
<li style="text-align: justify; font-size: 16px;
font-family: arial; line-height: 110%;"><a
href="http://arstechnica.com/tech-policy/2014/06/us-secret-service-wants-software-to-detect-sarcasm-on-social-media/">US
Secret Service wants software to "detect
sarcasm" on social media</a> (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, <a
href="http://consumerist.com/2014/06/04/you-could-be-the-person-who-builds-sarcasm-detection-software-for-the-secret-service-no-really/">The
Consumerist</a>'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.'"</li>
<li style="text-align: justify; font-size: 16px;
font-family: arial; line-height: 110%;"><a
href="http://www.bloombergview.com/articles/2014-06-06/even-secret-service-computers-don-t-get-sarcasm">Even
Secret Service computers don't get sarcasm</a>
(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 <a
href="http://blog.mashape.com/post/48757031167/list-of-20-sentiment-analysis-apis">some
developers claim higher rates</a>."</li>
<li style="text-align: justify; font-size: 16px;
font-family: arial; line-height: 110%;"><a
href="http://engineering.stanford.edu/news/stanford-algorithm-analyzes-sentence-sentiment-advances-machine-learning">Stanford
algorithm analyzes sentence sentiment,
advances machine learning</a> (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."</li>
</ul>
<div style="text-align: left;"> </div>
<p style="text-align: left; font-size: 20px;
font-family: arial; line-height: 110%;"><small><strong><em>Articles
via <a href="http://ohioweblibrary.org">Ohio
Web Library</a>:</em></strong></small><br>
</p>
<div style="text-align: justify; font-size: 16px;
font-family: arial; line-height: 110%;">
<ul>
<li><a
href="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">Mine
your language</a>. (<em>New Scientist</em>,
11/3/2012, p19/Douglas Heaven)</li>
<li><a
href="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">So
So Dataied</a>. (<em>New Republic</em>,
4/8/2013, p63/Leon Wieseltier)</li>
<li><a
href="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">Techniques
and Applications for Sentiment Analysis</a>.
(<em>Communications of the ACM</em>, April
2013, p82-89/Ronen Feldman)</li>
</ul>
</div>
<div style="text-align: left;"> </div>
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