[{"data":1,"prerenderedAt":326},["ShallowReactive",2],{"project-3901058":3},{"id":4,"name":5,"line":6,"line_source":7,"title":8,"url":9,"domain":5,"maker":10,"posted_at":11,"year":12,"points":13,"comments":14,"rank_in_year":15,"shown_in_year":16,"top":17,"tier":18,"category":19,"subcategory":20,"format":21,"keywords":22,"reception":28,"sentiment":29,"stance_mix":30,"scored_comments":35,"aspects":36,"strip":42,"post_text":43,"what":44,"said":77,"maker_in_thread":182,"shape":192,"grid":197,"attempts":288,"same_week":289,"maker_shows":32,"maker_hidden":318,"reader_version":319,"card":320},"3901058","friggeri.net","Beautiful Visualization of Agreement Groups in the US Senate","title","Show HN: Beautiful Visualization of Agreement Groups in the US Senate","http:\u002F\u002Ffriggeri.net\u002Fsenate\u002F","friggeri",1335561364,2012,95,39,230,1677,14,"notable","data","political voting visualization","web_app",[23,24,25,26,27],"us senate","voting groups","agreement visualization","roll call votes","political analysis","curious",0.222,{"positive":31,"neutral":32,"mixed":33,"critical":34},5,9,3,1,18,{"execution":37,"idea":39,"design":40,"docs":41},{"positive":34,"critical":38},0,{"positive":34,"critical":38},{"positive":33,"critical":34},{"positive":38,"critical":38},[38,38,38,33,38,33,38,38,33,38,33,33,38,38,38,38,33,33,38,38,31,38,38,38,38,31,31,34,38,33,38,33,38,33,38,31,33,31,33],null,{"problem":45,"audience":43,"pricing":43,"motivation":55,"time_to_build":43,"stack":59,"openness":74,"stage":75,"team_size":76},{"value":46,"source":47,"evidence":48},"Shows how US Senators group by voting agreement over time","maker",[49,52],{"id":50,"by":10,"text":51},"3901148","Op here, this is part of my PhD research. Please bare in mind that I'm French and that my knowledge of U.S politics is limited to what I can read online. If you find any errors…",{"id":53,"by":10,"text":54},"3901346","Thanks, the algorithm is a heuristic which optimize a quantity I've called social cohesion (http:\u002F\u002Farxiv.org\u002Fpdf\u002F1107.3231.pdf), the article presenting the algorithm itself is…",{"value":56,"source":47,"evidence":57},"Part of the maker's PhD research",[58],{"id":50,"by":10,"text":51},[60,68],{"value":61,"source":62,"evidence":63},"SVG","commenter",[64],{"id":65,"by":66,"text":67},"3901468","LyleK","Best use of SVG I have seen yet!",{"value":69,"source":47,"evidence":70},"TypeKit",[71],{"id":72,"by":10,"text":73},"3901448","I have absolutely no idea why it renders this way on your Chrome, maybe an issue with TypeKit? About the visualization, it was done semi-manually with a tool I've developed to…","unknown","launched","solo",{"praise":78,"objections":95,"requests":114,"questions":144,"alternatives":157},[79,91],{"value":80,"source":62,"evidence":81},"Visualization looks nice and well done",[82,86,87],{"id":83,"by":84,"text":85},"3901274","EvilTerran","It does look nice... and it does raise interesting questions. I'm particularly intrigued as to John Kerry, John Edwards, and Joe Lieberman's presences in that anomalous 108th…",{"id":65,"by":66,"text":67},{"id":88,"by":89,"text":90},"3901575","pacmon","Looks really great and seems like a useful tool. My only real complaint, is that I use a high sensitivity on my mouse and I found it difficult to highlight a line. If you could…",{"value":92,"source":62,"evidence":93},"Useful tool",[94],{"id":88,"by":89,"text":90},[96,103,107],{"value":97,"source":62,"evidence":98},"Left-right placement of parties is reversed",[99],{"id":100,"by":101,"text":102},"3901567","anigbrowl","It's very good, but suffers from one basic presentational error: You've placed Republicans on the left and Democrats on the right. While I know your algorithm doesn't attempt to…",{"value":104,"source":62,"evidence":105},"Groups are hard to select with a high-sensitivity mouse and lines are thin",[106],{"id":88,"by":89,"text":90},{"value":108,"source":62,"evidence":109},"Background bars too light and branching lines unclear",[110],{"id":111,"by":112,"text":113},"3901289","sesqu","For what it's worth, I thought the gray background bars were far too light - it took me a while to find them. I also couldn't intuit what the branching lines were all about.…",[115,126,137],{"value":116,"source":62,"evidence":117},"Explain the algorithm and how agreement groups are defined",[118,119,122],{"id":83,"by":84,"text":85},{"id":120,"by":112,"text":121},"3901395","Here's a screenshot from my Chrome 18 on Linux: http:\u002F\u002Fi.imgur.com\u002FvPwl8.png The visualization is quite nice, and it would be useful to link to or include some kind of short…",{"id":123,"by":124,"text":125},"3901310","joshu","Good stuff. Can you talk more about the algorithm? Can you use this to detect issue clusters rather than voting clusters? I have tried to build subgroup-in-graph detectors with…",{"value":127,"source":62,"evidence":128},"Apply the method per issue rather than per vote",[129,130,134],{"id":123,"by":124,"text":125},{"id":131,"by":132,"text":133},"3901552","specialist","Great stuff. Thanks for sharing. It'd be great to apply your algorithm per issue. During Camp Wellstone training (grassroots political organizing), they taught us a tool called a…",{"id":135,"by":124,"text":136},"3901645","You have a bipartite graph of bills and representatives. You use co-voting for the similarity metric to cluster representatives. Flip that around and cluster the bills using…",{"value":138,"source":62,"evidence":139},"Account for reelection cycles and party control",[140],{"id":141,"by":142,"text":143},"3901524","msg","Which sets of Senators were facing election that year? As a rule, only approximately a third. It would be nice to see if they were correlated to the group \"switching\" sides.…",[145,153],{"value":146,"source":62,"evidence":147},"Why Democrats appear in the Republican group in the 108th Congress",[148,152],{"id":149,"by":150,"text":151},"3901275","toyg","> One unexplicable point remains in the data and that is the presence of 18 Democrats in the Republican group of the 108th Congress. Dude, check the dates. Two words: Iraq…",{"id":83,"by":84,"text":85},{"value":154,"source":62,"evidence":155},"How agreement groups are defined",[156],{"id":83,"by":84,"text":85},[158,164,168,175],{"value":159,"source":47,"evidence":160},"Sankey diagrams and Minard's Napoleon map",[161],{"id":162,"by":10,"text":163},"3901330","I was not aware of this xkcd comic, funny how things seem to pop out. My inspiration was more in the line of Sankey diagrams. Among others, the famous map of Napoleon's invasion…",{"value":165,"source":62,"evidence":166},"XKCD comic 657",[167],{"id":83,"by":84,"text":85},{"value":169,"source":62,"evidence":170},"Simon Jackman ideal point estimates",[171],{"id":172,"by":173,"text":174},"3901647","caf","Simon Jackman calculates ideal point estimates based on non-unanimous roll calls: http:\u002F\u002Fjackman.stanford.edu\u002Fideal\u002FcurrentSenate\u002Fx1.pdf I think his R source is available too.",{"value":176,"source":62,"evidence":177},"Principal component analysis of Senate voting",[178],{"id":179,"by":180,"text":181},"3901479","drx","Would be interesting to see PCA and CA* applied to the same data. On a quick google trip I found [1] Principal Component Analysis of Senate Voting Patterns…",{"comments":183,"answered":31,"key":184},10,[185,186,189],{"id":50,"text":51},{"id":187,"text":188},"3901299","I thought about that, but 12 of the 18 Democrats were fiercely opposed to the invasion…",{"id":190,"text":191},"3901391","I'll have to go back to my notes, but I'm pretty sure I found a lot of opponents, but maybe I'm remembering wrong. Thank for pointing this out, I'll have another closer look !",{"commenters":193,"max_depth":194,"maker_replies":183,"first_comment_mins":195,"lifespan_hours":196},21,6,30,37,[198,202,205,207,209,210,212,213,217,219,221,223,227,231,233,236,239,242,245,249,251,253,255,257,258,260,262,264,266,269,270,271,274,275,277,278,280,281,284],[199,38,38,200,201,38],"3901838","other\u002Fneutral\u002Fnone","uptown",[203,38,38,200,204,38],"3902803","OstiaAntica",[50,34,38,206,10,34],"maker\u002Fneutral\u002Fnone",[149,34,33,208,150,38],"maker\u002Fneutral\u002Fexecution",[187,34,38,208,10,34],[211,34,33,208,150,38],"3901371",[190,34,38,208,10,34],[214,34,38,215,216,38],"3901556","commenter\u002Fneutral\u002Fnone","eaurouge",[141,34,33,218,142,38],"maker\u002Fneutral\u002Fidea",[220,34,38,218,10,34],"3901547",[100,34,33,222,101,38],"project\u002Fmixed\u002Fdesign",[224,34,33,225,226,38],"3901773","maker\u002Fmixed\u002Fdocs","Cushman",[228,34,38,229,230,38],"3901814","commenter\u002Fneutral\u002Fdocs","noahc",[232,34,38,229,226,38],"3901836",[234,34,38,229,235,38],"3903359","georgefox",[237,34,38,238,10,34],"3901835","maker\u002Fneutral\u002Fdocs",[240,34,33,238,241,38],"3901778","_delirium",[179,243,33,244,180,38],2,"project\u002Fneutral\u002Fidea",[246,243,38,247,248,38],"3901534","other\u002Fneutral\u002Fidea","olihb",[250,243,38,218,10,34],"3901542",[83,33,31,252,84,38],"project\u002Fpositive\u002Fdesign",[254,33,38,215,150,38],"3901295",[256,33,38,215,84,38],"3901307",[162,33,38,218,10,34],[259,33,38,200,132,38],"3901540",[261,33,31,252,84,38],"3905653",[88,263,31,252,89,38],4,[111,31,34,265,112,38],"project\u002Fcritical\u002Fdesign",[267,31,38,268,10,34],"3901352","maker\u002Fneutral\u002Fdesign",[120,31,33,222,112,38],[72,31,38,268,10,34],[272,31,33,273,112,38],"3901515","project\u002Fneutral\u002Fdesign",[172,194,38,200,173,38],[123,276,33,218,124,38],7,[53,276,38,218,10,34],[131,276,31,279,132,38],"project\u002Fpositive\u002Fidea",[135,276,33,244,124,38],[65,282,31,283,66,38],8,"project\u002Fpositive\u002Fexecution",[285,32,33,286,287,38],"3901681","project\u002Fneutral\u002Fnone","rorrr",[],[290,294,299,304,309,313],{"id":291,"name":292,"points":293,"category":19},"3910304","Million Short",552,{"id":295,"name":296,"points":297,"category":298},"3896931","iPG",290,"learning_science",{"id":300,"name":301,"points":302,"category":303},"3908844","cv",166,"productivity",{"id":305,"name":306,"points":307,"category":308},"3905318","Beatbar",147,"creative",{"id":310,"name":311,"points":312,"category":298},"3906373","Teach Yourself To Code",102,{"id":314,"name":315,"points":316,"category":317},"3896283","LiquidGraph",101,"ai",false,"v2",{"id":321,"name":5,"line":6,"ai":318,"cat":19,"year":12,"points":13,"comments":14,"rec":28,"s":322,"top":17,"kw":323,"maker":10,"domain":5,"tier":18,"attempts":38,"strip":324,"url":9,"mix":325,"praise":80,"objection":97,"sub":20},3901058,0.22,[23,24,25,26,27],"000303003033000033005000055103030305353",[31,32,33,34],1793990880919]