Social Network Analysis With R At National Chung Hsing University

1. SOCIAL NETWORK ANALYSIS WITH R
David Chiu @ 中興大學

2. ABOUT ME
Co-founder of NumerInfo
Trend Micro Engineer
ywchiu-tw.appspot.com

3. AGENDA
What is Social Network?
Why to Analyze Social Network?
How to Analyze
Social Network Connection (Oauth, Oauth2, OpenID)
Social Network Analysis With R
Social Network Visualization (Gephi)
Facebook Post Liked Analysis
Conclusion

4. SOCIAL NETWORK
http://libeltyseo.com/wp-content/uploads/2013/03/social-networking.png

5. HUMAN NATURE
http://cdn.macado.com/assets/2010/03/peeping-tom.gif

6. WHAT DO WE WANT TO KNOW?
Who knows whom, and which people are common to their
social networks?
How frequently are particular people communicating with one
another?
Which social network connections generate the most value for
a particular niche?
How does geography affect your social connections in an
online world?
Who are the most influential/popular people in a social
network?
What are people chatting about (and is it valuable)?
What are people interested in based upon the human language
that they use in a digital world?

7. EXPLORE FACEBOOK

8. LESSON 1: CONNECT TO SOCIAL NETWORK
OAuth Flow
Oauth v.s. OAuth2
OpenID

9. OAUTH FLOW
Open standard for authorization. OAuth provides a method for
clients to access server resources on behalf of a resource owner

10. DIFFERENCE BETWEEN OAUTH AND OAUTH2
More OAuth Flows to allow better support for non-browser
based applications
OAuth 2.0 no longer requires client applications to have
cryptography
OAuth 2.0 signatures are much less complicated
OAuth 2.0 Access tokens are "short-lived"
OAuth 2.0 is meant to have a clean separation of roles
between the server responsible for handling OAuth requests
and the server handling user authorization

11. OPENID
Open standard that allows users to be authenticated by certain
co-operating sites

12. CONNECT TO FACEBOOK
https://developers.facebook.com/

13. GET ACCESS TOKEN
https://developers.facebook.com/tools/explorer/

14. USER PERMISSION

15. PERMISSION LIST
User Data Permissions:
user_hometown
user_location
user_interests
user_likes
user_relationships
Friends Data Permissions:
friends_hometown
friends_location
friends_interests
friends_likes
friends_relationships
Extended Permissions:
read_friendlists

16. COPY TOKEN

17. LESSON 2: SOCIAL NETWORK ANALYSIS WITH
R
Let's Hack

18. REQUIRED PACKAGES
RCurl
General network (HTTP/FTP/...) client interface for R
rjson
JSON for R
XML
Tools for parsing and generating XML within R and S-Plus
igraph
Network analysis and visualization
bitops
Bitwise Operations

19. REQUIRED PACKAGE
i sa lp ca e( ( rs n,Ru l ,X L, ir p'' io s) dp ne c e= RE
n tl . ak gs c' jo ''C r' 'M ' ' g ah,b tp ' ,e ed ni sT U)
l ba yr sn
i rr ( jo )
l ba yR ul
i rr ( Cr )
l ba yX L
i rr ( M)
l ba yi rp )
i rr ( ga h
l ba yb tp )
i rr ( io s

20. FACEBOOK CONNECT
f _o nc < f nt o ( p t = " e, ac s_ oe = tk n ot os {
b cn e t - u c in a h
m" ce s tk n
o e, p in )
i ( !i sn (p i n) )
f m si go to s {
o to s< s rn f "% " ps e nm s o to s ,"" ul s( pi n) c la s ="
p i n - p i t( ?s, a t( ae ( pi n) =, ni to t os , ol pe
&
o to s< g u( ,, "2 " o to s
p i n - s b "" %C, p in )
u l< s rn f "t p: / r p .a eo kc m% % &c es tk n % " pt , ot os a c
r - p it ( ht s /g ah fc bo . o/ssac s _o e= s, a h pi n , c
}e s {
le
u l< s rn f "t p: / r p .a eo kc m% ? ce st kn %" p t, a cs _o e )
r - p it ( ht s /g ah fc bo . o/sa cs _ oe=s , ah c es t kn
}
dt < gt R ( u l s l vr fp e =F LE )
aa - e UL r , s. ei y er
AS
fo JO (d t )
rm S N aa
}

21. TEST ON API EXPLORER

22. EXECUTED RESULT
> f_ on c( m" a cs _o e)
bc n et "e ,c es t kn
$d
i
[ ]" 72 48 "
1 7 8 28 9
$ ae
nm
[ ]" ai C i"
1 Dvd hu
$ is _a e
f rt n m
[ ]" ai "
1 Dvd
$ at nm
l s_ a e
[ ]" hu
1 Ci"
$ ik
ln
[ ]" tp :/ w. a eo kc mC i Y"
1 h t s/ ww fc bo . o/ hu W
$ sr ae
u en m
[ ]" hu W
1 C i Y"

23. GET FRIEND LIST
> fi ns < f_ on c (a h" ef in s,a cs _o e=c es tk n
re d - bc n et pt =m / re d" c es t kn ac s_ oe )
> fi ns
re d

24. GET FRIEND GROUP LIST
f in go p < f _ on c( pt = m/ re di t" a cs _ oe =c es tk n
r ed r us - bc ne t a h" ef in l ss, ce st kn ac s _o e)
f in go p. d < sp l (r ed ru s d t,f nt o()xi)
r ed r us i
- a py fi n go p$ aa u c inx $d
f in go p. ae < sp l (r ed ru s d t,f nt o()xn m)
r ed r us nm - a py fi n go p$ aa u c inx $a e

25. FACEBOOK ELEMENT EXTRACTOR
# Gt Fi ns If r ai nF o F
e r ed n om to rm B
m < f_ on c( a h" e, ac s _o e= ce st k n o t osls (f ed ""d nm ,o
e - b cn et pt =m " c es tk na c s_ oe , pi n=it " il s=i, a el c
m nm < m$ ae
y ae - e nm
f in s< m $r ed
r ed - e fi n s
# Et at Fc bo I s
xr c a eo k D
f in si < sp l (r ed $a a fn to ( )x i)
r ed . d - a py fi n sd t , u ci nx $ d
# Et at F Mt I fr ai n
xr c B ea n om t o
f in sn m < u l s( ap yf i ns dt ,f nt o () i ov xn m , o' T 8, u= " )
r ed . ae - ni ts p l( re d$ aa uc in x
c n( $a e t= UF 's b " ) )
f in sg ne < s pl (r ed $ aa fn t o( )u ls ( fi . u l x gn e ) " o e e
r ed . ed r - a py f in sd t, u ci nx ni ti (s nl ( $e dr ) nn " l
f in sl ct o. d < u l s( ap yf in s dt,f nt o () xl ct o$ d )
r ed . oa in i - ni ts p l( re d$ aa uc in x $o a in i)
f in sl ct o. a e< u ls (a py fi n sd t , fn t o( ){ f( s n l ( $ oa in
r ed . oa in nm - n it s pl (r ed $a a u ci nx i i. ulxl c to$
f in sh mt w. a e< u ls (a py fi n sd t , fn t o( ){ f( s n l ( $ oe on
r ed . oe on nm - n it s pl (r ed $a a u ci nx i i. ulxh m tw$

26. GET FRIENDSHIP MATRIX
f in si s< f nt o( {
r ed h p - u c in )
pi t" ee ai g fi ns i mt i"
rn ( Gn rt n re d hp a rx)
N< l nt (r ed .d
- e gh fi n si )
fi ns i. ar x < m t i(,, )
re d hp mt i - ar x0N N
fr ( i 1N {
o i n :)
p it ps ei f in sn m[ ] )
r n (a t( ,r ed . ae i)
t p< f cb o( pt = at (m /u ul r ed " fi nsi [ ] sp"" , ac s _o e
m - a e o k a h p s e " e m t a f i n s , r e d . d i , e =/ )
c es tk
m ta fi ns < sp l (m $a a fn to () xi)
u u lr ed - a py tp d t, uc i nx $d
f in si .a r xi fi ns i %n m ta fi n s < 1
r e dh pm ti [, r ed .d i % u u lr ed ] }
#C et c ne to sw t m fi ns
r a e o nc i n ih y r ed
fi ns cn < c1N
re d _o - ( :)
fi ns cn ]< 1
re d _o [ #A dt i vc o a a c lm t te fi n si m ti
d hs et r s
o un o h r ed hp a rx
fi ns i. ar x < c i df in si .a r xf in sc n
re d hp mt i - bn (r e dh pm ti ,r e d_ o)
#A pn m fi n si w t m s l
p e d y r ed hp i h ye f
fi ns i. ar x < r i df in si .a r xa pn (r e d_ o, )
re d hp mt i - bn (r e dh pm ti ,p e df in sc n 0 )
rw ae (r ed h pm ti )< a pn (r e d. aemn m )
on m sf in si .a r x - pe df in sn m,y ae
cl ae (r ed h pm ti )< a pn (r e d. aemn m )
on m sf in si .a r x - pe df in sn m,y ae
rt r (r ed hpmt i )
eu n fi ns i.a rx
}

27. FRIEND GRAPH
f in ga h< f nt o( r ed hpmt i ) {
r ed r p - u c in fi ns i.a rx
f i n s i . r p < g a h a j c n y f i n s i . a r x m d = (u d r c e " , w i h e =
re d hp ga h - r p.d ae c ( re d hp mt i, o ec"n i et d) e g tdN
Vf in si .r p )g ne < a pn (r ed .e d r m s l$ ed r
(r e dh pg ah $e d r - p ed fi n sg ne , ye fg ne )
V f i n s i . r p ) l c t o < a p n ( r e d . o a i nn m , m s l $ o a i n n m )
(r e dh pg ah $o a in - pe df i ns lc to . ae y ef lc t o$ ae
V f i n s i . r p ) h m t w < a p n ( r e d . o e o nn m , m s l $ o e o n n m )
(r e dh pg ah $o e on - pe df i ns hm tw . ae y ef hm t w$ ae
Vf in si .r p )L bl < Vf in si . rp )n m
(r e dh pg ah $a e - ( re dh pg ah $ ae
rt r ( re dh p ga h
eu n fi ns i. rp )
}

28. DRAW FRIENDSHIP GRAPH
f mt i < f in s is )
_ ar x - re dh p(
f ga h< f in ga hf m ti)
_ rp - r ed r p( _a rx
w ie ga hf ga h "r e d. rp m" fr a =g ah l )
r t. r p ( _r p, f in sg a hl ,o mt "r p m"

29. GRAPH XML FORAMT (GRAPHML)

30. LESSON 3: SOCIAL NETWORK VISUALIZATION
Using Gephi

31. GEPHI
Gephi, an open source graph visualization and manipulation
software

32. MODULARITY
Measure of the structure of networks or graphs. It was
designed to measure the strength of division of a network into
modules
Networks with high modularity have dense connections
between the nodes within modules but sparse connections
between nodes in different modules

33. LEARN MORE ABOUT GEPHI
https://www.udemy.com/gephi/

34. GET LIKES COUNT OF POSTS
r qi ep y)
e ur ( lr
p ss < f_ on c( ah " ep ss ,a cs _ oe =c es t kn ot o sl s( fe d "" i
o t - bc ne t pt =m /o t " ce st kn a cs _o e, p in =i t "i ls =l
p s. ie < sp l (o t$ aa f nt o( ) xl ks
o tl k s - a py ps s dt , uc in x $i e )
p s. ie .a a< s pl ( ot lk s fn to () x dt )
o tl k sd t - ap yp s. i e, uc i nx $ aa
l =l s (
i
it )
f r( i 1l nt ( ot lk sd t ){
o i n : eg hp s. i e. aa )
fr ( i 1(e g hp s. ie . aa [])1)
o j n :l nt (o t lk sd t [ i]- ){
l < a p n ( i p s . i e . a a [ ] [ j ]n m )
i - p ed l, o tl ks d t[ i] []$a e
}
}
d =d. al ri dd t. r m, l)
f
oc l( bn . aa fa e i
c la e( f < c " ae )
o nm s d) - (n m"
d py d, .n m) s ma i e N m us =l nt (a e )
d l( f ( ae , um rz , uS b
e g hn m)

35. CONCLUSION REMARK
Interesting Fact Abour Friends
Value Behind The Network
Statstic Is Worth More Than Thousand of Words

36. YOUR TURN TO DO SOME ANALYSIS
Find Popular Checkins Among Your Friends
Common Interest Between Your Friends
Female/Male Distribution of Your Know Friends
Most Pupular Photos Being Liked
Asociation Rule of Friends (Gossip)

37. THANK YOU