Social Network Analysis With R
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This document outlines an agenda for analyzing social networks with R. It discusses connecting to social networks like Facebook via APIs, extracting friend data, creating a friendship matrix, and visualizing the resulting friend graph in Gephi. It also provides examples of analyzing Facebook data like extracting post likes counts and generating statistics on popular posts. The document encourages exploring one's own social network data to find insights like common interests between friends or the gender distribution of one's network.
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Social Network Analysis With R
- 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
- 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?
- 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
- 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