extensions [ nw ] globals [ centralities leader leader-news ] turtles-own [ source belong-to ;;news belong to whome centrality newscolor ;;initial news color red nodecolor ;;original color user-name num-of-news tag ] breed [news a-news] breed [people node] breed [mouse mice] mouse-own [click ] ;;red 15, pink 135, blue 105, yellow 45 to startup hubnet-reset end to setup clear-all create-people 1 [set color 15 set nodecolor 15 set shape "circle" set size 0.6 set user-name "computer 0" set tag 0] create-people 1 [set color 15 set nodecolor 15 create-link-with turtle 0 set shape "circle" set size 0.6 set user-name "computer 1" set tag 0] ask one-of turtles[set color 135] let newscreater turtles with [color = 135] nw:set-snapshot turtles links cal-centrality newscreater setup-news ask news [put-ontop] set centralities [] set leader "" set leader-news 0 ;set centralities fput [centrality] of newscreater centralities ;set noderead fput 1 noderead reset-ticks end ;;prefential attachment to setup-initial-network [old-node] create-people 1 [ set color 15 set user-name hubnet-message-source set nodecolor 15 set num-of-news 0 set tag 1 set shape "circle" set size 0.6 if old-node != nobody [ create-link-with old-node ;; position the new node near its partner move-to old-node fd 8 ] ] end to-report find-partner let total random-float sum [count link-neighbors] of turtles let partner nobody ask turtles [ let nc count link-neighbors ;; if there's no winner yet... if partner = nobody [ ifelse nc > total [ set partner self ] [ set total total - nc ] ] ] report partner end ;;;;;;;;;;;;;;;;;;;;;;;;; to setup-news create-news 1 [ set shape "square" set color 45 ;;yellow set newscolor 15 set num-of-news 0 set size 1 set source one-of turtles with [color = 135] ] let temp one-of turtles with [color = 135] ask news [move-to temp set belong-to temp] end to spreadnews listen-clients ifelse ticks mod 4 = 0 and ticks > 0 [ let countgreen count people with [color = 65] let countpink count people with [color = 135] let countgrey count people with [color = 9] let countsame countgreen + countpink let countdiff countgrey let countread countsame + countdiff let creater [source] of one-of news ;;set noderead fput countread noderead set centralities fput(list [centrality] of creater countread) centralities ask news [die] ask turtles [set color nodecolor] ask one-of people [set color 135] let newscreater turtles with [color = 135] setup-news cal-centrality newscreater ;set centralities fput [centrality] of newscreater centralities ] [ ask turtles with [color = 135] [ while [count link-neighbors with [color = 15 or color = 105] > 0] [ let spread one-of link-neighbors with [color != 135] ;;node we are going to spread let parent one-of turtles-here with [color = 45] ;;news to be spread if spread != nobody [ ifelse [newscolor] of parent = [color] of spread [ ask spread [set color 65 set num-of-news num-of-news + 1] ;; the people with same opinion read the news green if random-float 100 < news-is-interesting [ ask spread [set color 135] ask parent[hatch 1] ask parent [move-to spread set belong-to spread] ]] [ ask spread [set color 9] ;; the people with different opinion read the news grey ] ] ] ] ] update-leader-stats ask people with [user-name = hubnet-message-source] [send-student-info] tick end to put-ontop hatch 1;;[create-links-with [links]of myself] die end to layout ;; the number 3 here is arbitrary; more repetitions slows down the ;; model, but too few gives poor layouts repeat 3 [ ;; the more turtles we have to fit into the same amount of space, ;; the smaller the inputs to layout-spring we'll need to use let factor sqrt count turtles ;; numbers here are arbitrarily chosen for pleasing appearance layout-spring turtles links (1 / factor) (7 / factor) (1 / factor) display ;; for smooth animation ] ;; don't bump the edges of the world let x-offset max [xcor] of turtles + min [xcor] of turtles let y-offset max [ycor] of turtles + min [ycor] of turtles ;; big jumps look funny, so only adjust a little each time set x-offset limit-magnitude x-offset 0.1 set y-offset limit-magnitude y-offset 0.1 ask turtles [ setxy (xcor - x-offset / 2) (ycor - y-offset / 2) ] ask news [move-to [belong-to] of self] end to-report limit-magnitude [number limit] if number > limit [ report limit ] if number < (- limit) [ report (- limit) ] report number end to resize-nodes ifelse all? turtles [size <= 1] [ ;; a node is a circle with diameter determined by ;; the SIZE variable; using SQRT makes the circle's ;; area proportional to its degree ask turtles [ set size sqrt count link-neighbors ] ] [ ask turtles [ set size 1 ] ] end to cal-centrality [choice] ifelse centrality-measure = "degree-centrality" [ask choice [ set centrality count my-links ] ] [ ask choice[ set centrality runresult (word "nw:" centrality-measure) ] ] ;;report [centrality] of choice end to cal-local-cluster [choice] ask choice [let num-nei one-of link-neighbors with [color = 15] ] end to two-color ask people with [who mod 2 = 0] [ if color != 135 [ set color 105 set nodecolor 105 ] ] end to listen-clients while [hubnet-message-waiting?] [ hubnet-fetch-message ifelse hubnet-enter-message? [ add-node ] [ ifelse hubnet-exit-message? [ remove-node ] [ if hubnet-message-tag = "View" ;;????? [ ask people with [ user-name = hubnet-message-source ] [ change-connect ] ] ] ] ] end to change-connect let clicked-xcor (item 0 hubnet-message) let clicked-ycor (item 1 hubnet-message) ask mouse with [ user-name = hubnet-message-source ] [ set xcor clicked-xcor ;; go to the location of the click set ycor clicked-ycor set click people in-radius 1 ] ask people with [ user-name = hubnet-message-source ] [ if one-of first [click] of mouse with [user-name = hubnet-message-source] != nobody [ ifelse first [link-neighbor? one-of first [click] of mouse with [user-name = hubnet-message-source]] of people with [ user-name = hubnet-message-source ] [ ask link-with one-of first [click] of mouse with [user-name = hubnet-message-source] [die] ] [ if count link-neighbors < allowed-link [ create-link-with one-of first [click] of mouse with [user-name = hubnet-message-source] ] ] ] ] end to add-node setup-initial-network find-partner create-mouse 1 [ set user-name hubnet-message-source set color black ] end to remove-node ask people with [ user-name = hubnet-message-source ] [ die ] end to update-leader-stats let leaders people with [tag = 1]with-max [num-of-news] let number-leaders count leaders if one-of leaders != nobody [ ifelse number-leaders > 1 [ set leader word number-leaders "-way tie" ] [ ask one-of leaders [ set leader user-name ] ] set leader-news [num-of-news] of one-of leaders ] end to send-student-info ;; player procedure hubnet-send user-name "Your name" user-name hubnet-send user-name "Number of news you received" num-of-news hubnet-send user-name "Top Twitterer" leader hubnet-send user-name "Top twitterer's news" leader-news end @#$#@#$#@ GRAPHICS-WINDOW 502 15 998 520 40 39 6.0 1 10 1 1 1 0 1 1 1 -40 40 -39 39 1 1 1 ticks 30.0 BUTTON 21 152 84 185 NIL setup NIL 1 T OBSERVER NIL NIL NIL NIL 1 SLIDER 20 65 193 98 news-is-interesting news-is-interesting 0 100 38 1 1 % HORIZONTAL PLOT 223 188 423 367 num people read news vs tick tick # of people read news 0.0 20.0 0.0 200.0 true false "" "" PENS "default" 1.0 0 -16777216 true "" "plot count turtles with [color = pink or color = 69]" BUTTON 21 193 116 226 redo layout layout T 1 T OBSERVER NIL NIL NIL NIL 1 BUTTON 21 235 123 268 NIL resize-nodes NIL 1 T OBSERVER NIL NIL NIL NIL 1 CHOOSER 20 13 192 58 centrality-measure centrality-measure "degree-centrality" "betweenness-centrality" "eigenvector-centrality" "closeness-centrality" "random" 0 PLOT 223 12 474 180 num people read news vs Centrality Centrality # People read news 0.0 0.0010 0.0 1.0 true false "" "" PENS "default" 1.0 2 -16777216 true "" "if length centralities > 0\n[\nplotxy first first centralities last first centralities\n]" BUTTON 21 278 104 311 NIL two-color NIL 1 T OBSERVER NIL NIL NIL NIL 1 BUTTON 21 323 119 356 NIL spreadnews T 1 T OBSERVER NIL NIL NIL NIL 1 BUTTON 21 366 150 399 spreadnews-once spreadnews NIL 1 T OBSERVER NIL NIL NIL NIL 1 MONITOR 223 375 309 420 Top twitterer leader 17 1 11 MONITOR 223 434 407 479 number of top twitterer's news leader-news 17 1 11 SLIDER 20 107 194 140 allowed-link allowed-link 0 10 4 1 1 NIL HORIZONTAL @#$#@#$#@ ## WHAT IS IT? This model is a HubNet activity complement to NetLogo model. We simulated social network sites. Each node represent a people in Online Social Network like twitter or facebook. The goal for this activity is to receive the largest number of news from network. ## HOW IT WORKS Each participate student is a node in the network. They can use their mouse in client to choose the people they want to follow (connect). They can relick that people to not follow him (disconnect). In this case the network will be a truly dynamic network where every one want to optimise their own network. We set the maximum possible number of people that one can follow. So that he has to make a choice. There is a life time for news. At the begining of life cycle, we will randomly pick a people as news creater. Rule for network growth: In each tick, every people that feels the news is interesting will twitter the news. We use a possibility to describe the agent behavior of “feeling interesting”. The news will be twittered to all the neighbors of the one who retwitter the news and these neighbors will read the news. If they feel the news is interesting, the will retwitter the news in next tick and they will follow the news creater. In this way the number of follower of the news creater increase. Rule for news spread: The rule is similar to network growth. The only difference is in this situation those people retwitte the news won’t follow the new creater. We use this mechanism to see how news being spread in a stable network. Rule for two different opinion: If we have two group of people with totally different opinion. Those people with different opinion will read the news and ignore it (never retwitter). ## HOW TO USE IT Centrality: Decide use which kind of centrality measurement News-is-interesting: Determing the probability of retwitter allowed link: the maximum number of people each person can follow News-life: The life cycle of news Setup: Initialize a scale free network according to preferential attachment. Redo layour: Layout the network according to its connectivility. resize node: resize the node according to the number of neighbors two-color: split the entire graph into two groups with different opinions. We use this buttom to start simluate news spread between two groups. Spreadnews: Forever running buttom to spread the news on network Spreadnews-once: run spread one tick Top twitter: the name of the client who received the largest number of news ## THINGS TO NOTICE Please do the activity according to the following sequence: 1. setup network 2. let all user login to the server 3. click Spreadnews buttom to start news This model use the NW extension. You can download the extension from “https://github.com/NetLogo/NW-Extension” ## THINGS TO TRY Try to adjust the allower number of links ## EXTENDING THE MODEL A possible further entension is to allow client to communicate so that this activity looks more like a real social network. ## NETLOGO FEATURES This model use the NW extension. Besides, the implementation use loop as flow control and list as data structure. ## RELATED MODELS There is a NetLogo Model direct related to this model. In the literature there are Rumer Propogating model which is related to this model. ## CREDITS AND REFERENCES You can find more about this model on modeling common.“http://modelingcommons.org/” Paper reference: [1] Dechun Liu; Xi Chen, “Rumor Propagation in Online Social Networks Like Twitter – A Simulation Study,” Multimedia Information Networking and Security (MINES), 2011 Third International Conference on , vol., no., pp.278,282, 4-6 Nov. 2011 [2] Barabási, A.L., R. Albert, and H. Jeong, Mean-field theory for scalefree random networks. Physica A: Statistical Mechanics and its Applications, 1999. 272(1-2): p. 173-187. [3] Suh, B.; Lichan Hong; Pirolli, P.; Chi, Ed H., “Want to be Retweeted? Large Scale Analytics on Factors Impacting Retweet in Twitter Network,” Social Computing (SocialCom), 2010 IEEE Second International Conference on , vol., no., pp.177,184, 20-22 Aug. 2010 [4] Stonedahl, Forrest, Rand, William M. and Wilensky, Uri, Evolving Viral Marketing Strategies (July 2010). GECCO 2010, Portland, Oregon, USA, July 7-11, 2010 ; Robert H. Smith School Research Paper No. RHS 06-133. [5] Joseph J. Pfeiffer , Jennifer Neville, Methods to Determine Node Centrality and Clustering in Graphs with Uncertain Structure, Fifth International AAAI Conference on Weblogs and Social Media. 9 pages, 4 Figures, 2 Apr 2011 @#$#@#$#@ default true 0 Polygon -7500403 true true 150 5 40 250 150 205 260 250 airplane true 0 Polygon -7500403 true true 150 0 135 15 120 60 120 105 15 165 15 195 120 180 135 240 105 270 120 285 150 270 180 285 210 270 165 240 180 180 285 195 285 165 180 105 180 60 165 15 arrow true 0 Polygon -7500403 true true 150 0 0 150 105 150 105 293 195 293 195 150 300 150 box false 0 Polygon -7500403 true true 150 285 285 225 285 75 150 135 Polygon -7500403 true true 150 135 15 75 150 15 285 75 Polygon -7500403 true true 15 75 15 225 150 285 150 135 Line -16777216 false 150 285 150 135 Line -16777216 false 150 135 15 75 Line -16777216 false 150 135 285 75 bug true 0 Circle -7500403 true true 96 182 108 Circle -7500403 true true 110 127 80 Circle -7500403 true true 110 75 80 Line 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