The document discusses the evolution of sentiment analysis in the context of social media, highlighting its importance for businesses in understanding public opinion on products, services, and various topics. It emphasizes the complexity of sentiment interpretation, including the influence of language, context, and cultural differences in conveying meaning. The author urges organizations to define their goals for sentiment analysis, ensure consensus on its meaning within teams, and consider the depth and accuracy needed for effective use of the data.

1. How
does
that
make
you
feel?
Social
sen6ment
analy6cs
in
2012
Catherine
H
van
Zuylen

2. Who
the
heck
are
you?
;-­‐)
A1ensity
is
in
the
business
of
making
social
media
truly
accessible
and
useful
for
the
enterprise.
We
process
millions
of
social
media
and
other
communica>ons
every
day,
including
the
full
Twi1er
firehose,
Facebook,
thousands
of
blogs,
forums,
and
review
sites,
along
with
surveys,
CRM
records,
etc.

3. This
growth
in
social
media
has
led
to
renewed
interest
in
sen:ment
§ News
and
opinions
about
everything…
§ Products
–
phones,
cars,
food…
§ Services
–
cable
companies,
telcos…
§ Popular
culture
(TV,
film,
music)
§ Poli:cs
§ Everyone
is
trying
to
use
social
to
predict
(or
explain)
outcomes
–
and
“sen:ment”
plays
a
big
role
in
this

4. “Sen:ment
Analysis”
used
to
be
simple
I
love
my
iPhone.
I
hate
brussels
sprouts.

5. But
:mes
have
changed
5 5/9/12 l Footer

6. Rela:ve
Sen:ment
My
car
died.
I
bought
an
iPhone.

7. Some:mes
nega:ve
sen:ment
isn’t
bad
7 5/9/12 l Footer

8. Posi:ve
feelings
about
actors
might
not
be
about
their
ac:ng
8 5/9/12 l Footer

9. Remember
when
“Document-­‐Based”
Sen:ment
Was
the
Standard?

10. Compound
Sen:ment
is
the
New
Reality

11. Ambiguity
and
new
uses
for
“nega:ve”
words
<-­‐
“Hate”
ends
up
being
posi6ve
about
the
singer
“holy
crap”
vs
“this
is
crap”
-­‐>
<-­‐
“amazing
as
f***”
11 5/9/12 l Footer

12. Small
change
in
voice
=
Big
change
in
meaning
Are
you
angry
about
the
way
Comcast
treated
you?
(Ques>on)
I
think
you
should
be
really
mad
about
this.
(Sugges>on)
If
someone
doesn't
call
me
back,
I'm
going
to
be
really
angry.
(Condi>onal)
I
was
really
mad
at
them,
but
then
they
offered
me
a
refund.
(Past)
I’m
not
angry
with
them;
I
just
want
them
to
help
me.
(Nega>on)
I
am
really
really
angry
about
this.
(Augment)
I’m
mad
at
them
AGAIN
because
they
keep
messing
up.
(Recur)

13. Sen:ment
Scoring
I
LIKE
THAT(+1)
I
LOVE
THAT
(+3)
I
HATE
THAT
(-­‐3)

14. Sen:ment
Scoring
I
REALLY
LIKE
THAT
(+2)
I
KINDA
LOVE
THAT
(??)

15. Emo:cons
as
Sen:ment
and
Modifiers
Bought
an
iPhone
today
:-­‐D
I
just
love
Comcast
;-­‐)

16. Seems
Easy
But…
(^_^)

17. (;_;)

18. It’s
the
LiVle
Differences

19. It’s
the
LiVle
Differences
Japanese
tend
to
use
emo:cons
with
expressive
eyes
and
a
neutral
mouth
^_^
while
Americans
do
the
opposite
:)
Americans
oen
badly
misinterpret
the
meaning
assigned
to
popular
emo:cons
from
Japanese
culture

20. And
accuracy
is
more
and
more
important.
Why?

21. Rou:ng
applica:ons
Someone
ha>ng
you
needs
to
go
to
your
contact
center
Someone
ha>ng
your
compe>tor
might
be
a
sales
lead

22. Forecas:ng
markets
Amalgamood

23. Forecas:ng
elec:ons
major
and
minor
23 5/9/12 l Footer

24. In
Summary
§ Think
about
what
your
goals
are
§ Make
sure
your
team
agrees
on
what
“sen:ment
analysis”
is…
or
agrees
to
disagree
§ What
are
you
going
to
do
with
the
data?
§ How
deep
do
you
need
to
go?
§ How
accurate
do
you
need
to
be?
24 5/9/12 l Footer

25. THANK
YOU
CATHERINE VAN ZUYLEN
CVANZUYLEN@ATTENSITY.COM
@CATEVZ