Self-Organizing the Eurovision

Training cycles 0/500

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0.9404330470133573,0.14546888158656657,0.9392439601942897,0.5282391582150012,0.22293902514502406,0.5896013544406742,0.5422858560923487,0.5085516788531095,0.214141049887985,0.8422721643000841,0.185159811982885,0.4888711136300117,0.2162809236906469

0.6282095392234623,0.5838618215639144,0.9350689693819731,0.26706896000541747,0.3369024533312768,0.35891201347112656,0.09533988917246461,0.023307320894673467,0.12831304338760674,0.4565743412822485,0.055258986074477434,0.3205369918141514,0.10119795240461826

0.6572776448447257,0.6481076951604337,0.45640417793765664,0.8968778112903237,0.6167313435580581,0.8838873244822025,0.5371586247347295,0.15055121225304902,0.4419248467311263,0.6749367527663708,0.05101523897610605,0.8983757121022791,0.4665748057886958

0.4680658851284534,0.3106457272078842,0.9396249507553875,0.451580444118008,0.04042912437580526,0.9064407381229103,0.000010911142453551292,0.24938663165085018,0.22025041980668902,0.09247034275904298,0.2633534581400454,0.25191629584878683,0.9619505750015378

0.9300816881004721,0.4081619691569358,0.3328716706018895,0.7671131561510265,0.996571930591017,0.30994289042428136,0.4296894639264792,0.3508977845776826,0.6849867578130215,0.32739427080377936,0.07663250132463872,0.7224685484543443,0.9367634418886155

0.8430651715025306,0.6899973228573799,0.7008490753360093,0.2661777494940907,0.3157373536378145,0.772823543753475,0.8852334932889789,0.7903122105635703,0.32480784389190376,0.3358980680350214,0.21714115049690008,0.992615366121754,0.9036029260605574

0.09039712464436889,0.03559257462620735,0.5953158866614103,0.38411163608543575,0.658016319386661,0.9315089010633528,0.1854495699517429,0.7406234578229487,0.3546961103565991,0.2744088245090097,0.5080200028605759,0.511373607441783,0.10116295260377228

0.8844395410269499,0.299485546303913,0.9444113590288907,0.5598046411760151,0.4392873852048069,0.4675866994075477,0.4994347500614822,0.674234950216487,0.4115116863977164,0.5128814412746578,0.3110860420856625,0.9303182060830295,0.6309528967831284

0.5491145926553114,0.19524547118395397,0.7921930296326971,0.9019682889660283,0.5243360110797686,0.810055181777009,0.5800645640330646,0.1034963093336545,0.8691577930103748,0.18995740437923683,0.5601057780828438,0.6993565321156321,1.0402406377756006

0.6583035845556625,0.4127199823173373,0.5157614186022511,0.7734858299157531,0.521436164811299,0.6593438763162978,0.9032465556804676,0.6989474080891469,0.28216543055793986,0.4875169351281964,0.8407822111990448,0.9551165903154022,0.8687851045253764

1.1982239143737372,0.6671433354860646,0.545390219900388,0.6489124107598493,0.9589227611790326,0.2414039189608135,1.159309888351805,0.12764037767224629,0.6522394560297897,0.927024752211575,0.620933219352695,0.5014517871330118,0.43920868942352814

1.1672614248450652,0.19700772777160946,0.1360025151020125,0.7201853591329254,0.3850718854175976,0.3313386527772313,1.1718684598034765,0.760942599659291,0.4773950900333192,0.19226177945338407,0.9829748325250042,0.9983438006329656,0.2101249101969184

1.1489776713541953,0.578060759620377,0.1580885815664626,0.8063414334469114,0.39285874062596826,0.8107387073567209,0.7356790935191835,0.3766936237017642,0.6792129226537345,0.38421507453866477,0.724735932907485,0.487980216024053,0.22545906475719824

0.3686518743634224,0.5536007257178426,0.30869138496927917,0.7483135904185474,0.04704961134120822,0.3884078215342015,0.8147645834833384,0.19900703546591103,0.2865932888817042,0.2828433986287564,0.6284165938850492,0.17866846290417016,0.5057380094658583

0.7278593206829987,0.49531301625471014,0.7427985343717779,0.3758460867473765,0.0808572903587112,0.280375264199576,1.1673279647666739,0.968976739579645,0.7276793301275797,0.3324480781228888,0.4379906160249216,0.7900985481063306,0.6233592133317447

1.153512383465946,0.46971024753895996,0.9218161425190258,0.23668660809061237,0.8218452393738304,0.9754577845920132,1.1959632955130997,0.46813354590489537,0.8710154172483032,0.0711025834342916,0.6136062211627612,0.560111221270281,0.20664909614956462

0.9087087260582969,0.453794736535467,0.5703484229470179,0.8498485308637289,0.277129431229537,0.4330128113385702,1.0285764236614254,0.4928607916716267,0.7096797636759158,0.18122651131100323,0.8464135342054477,0.8204085111576294,0.4762657131257034

0.440408963966986,0.3275448354162568,0.4382421022325852,0.7440499391946805,0.556255047068566,0.5893487410661925,1.150539543361664,0.7164933285950212,0.5535852272986702,0.5724864141309979,0.13848192694877465,0.7023549481265612,0.9704112164982689

0.944621791436956,0.9469939115773335,0.9606642015842018,0.13092534281722185,0.12497661988126135,0.9857460808894438,0.7621656909711583,0.7096381103651915,1.1602641424449227,0.9814503134192157,0.10132998698316456,0.715923637686733,0.3808869256635509

1.1304967578955627,0.505618504879904,0.1804108936430642,0.42211143266753337,0.965936375424393,0.5589771397105258,0.5972318094986045,0.8664898183899623,0.5014165870407965,0.8322401194924224,0.38329157681994835,0.20205579067162083,0.904811949165698

1.1052219274141715,0.48079707745449385,0.07749324643715184,0.4664842906264641,0.14063778968858415,0.9192580889001363,1.0481999311263865,0.43463116130263335,1.116460555173386,0.109969825254624,0.10949411117332751,0.49193891746271623,0.6715243122235544

0.5230956708672073,0.784057944349984,0.9257572246926589,0.5153161710095888,0.18954252152374237,0.4248108151463748,0.8454737043501869,0.6328503302922176,0.9468105898568917,0.5417915343682375,0.6594847055174412,0.3462398703753672,0.8266828257321517

0.7580893939128401,0.8766949942700928,0.1509745484651493,0.36792006097934193,0.6274760983487455,0.8638804090205366,0.8076022883913685,0.28484137755219663,0.39734012698714677,0.08265222714167299,0.8510341058759514,0.9216336825664169,0.8037348218024456

0.7070861482061446,0.7962621678598225,0.5710203959606588,0.6087658342439681,0.18370351986959577,0.28861276316456497,0.5939412196166813,0.6932870096061379,0.05734857078641653,0.07654523337259889,0.9974675269331783,0.35179970506578684,0.07303684134967625

1.016193303003254,0.5697094231966343,0.5945044231573767,0.76211946987264,0.9698983299934476,0.3792858466834182,0.9507833374245838,0.2601093350552798,0.552017764616161,0.2017832347828875,0.11959576349207991,0.7834446696197025,1.0216995701867424

1.191589264362478,0.3149132374426955,0.6459928336489066,0.5285050777720106,0.7451620505309708,0.6233406453083644,0.9331100141707537,0.26557795684382773,1.0499341020394253,0.5068949131796673,0.19115595000679397,0.7588011240305079,0.38426850441193483

0.9133358884352246,0.6847574903400451,0.5562630012819513,0.38812336919569335,0.2091477654518079,0.9322657417569477,1.1658316482193591,0.0822252527457056,0.9473800034752348,0.6493378345780844,0.8288451929767481,0.20462641564819312,0.16731547034884364

1.0564472670543363,0.30064807184382464,0.9865643942038502,0.47411024874944124,0.656944923659959,0.7712569715858097,1.083880007939935,0.3410682093297117,0.36893594869855767,0.9076779331353926,0.20252988767139515,0.3767997367577115,0.7711950332765692

1.1342824130847375,0.599154493683769,0.40192785265199277,0.24647065853108763,0.2272040866746583,0.8413948410587041,0.5751440202967402,0.7014564138928322,0.3764334734334275,0.23403065175861332,0.12702906974848344,0.7652909653317475,0.8253636468386171

1.090856017912391,0.7402089063180932,0.520972128655556,0.8915717817506933,0.7557601782064977,0.881435858867722,0.9789624288409116,0.6597883043829318,1.2267323085335238,0.12018601673229959,0.48265552837654885,0.3150218836488696,0.7146295283124074

0.492672989701123,0.8001475586031881,0.3069120771006291,0.45188850685936605,0.22440148535512294,0.8766127665205556,1.1633981241002218,0.5682088727812056,0.8798479215188124,0.21311564388576698,0.49677045510699036,0.631548211217113,0.43852009595148495

0.3094517551664418,0.4351483119930769,0.8773542151975622,0.8384950781309193,0.1786487714851206,0.4077917450556716,1.2917897001766454,0.5479665172122047,1.1652171225877699,0.5348547151215673,0.6437081354607532,0.9882788405903573,0.9101918853961358

0.8757632052326794,0.06818217348229076,0.2428715835017507,0.960484131827394,0.3748350756121248,0.5762258482756734,0.744419909358673,0.2386723379555815,1.1253198400950486,0.6345733581000573,0.09120033246697747,0.1035624056776168,1.024769170134138

0.19146108929999173,0.14269752684049308,0.6620812993496656,0.32105665653944016,0.6220983853563666,0.29117372119799256,0.9340210407972336,0.47866075532510877,0.3697328041307628,0.19156057434156537,0.9075703490525484,0.4001656451728195,0.16591014876030385

0.6842347939588529,0.4497762985224465,0.6412509178624468,0.9210580740752659,0.4179903879794496,0.45015846619387473,0.35791610158562814,0.7651695112298186,0.9153377044278872,0.8162678166957996,0.3180632747102328,0.3849706683718698,0.3569600169212068

0.8374770388054076,0.5902658886118938,0.5579984675724252,0.2132905976688279,0.8716754191914242,0.22503188533476706,0.9037168663937254,0.8585644559308365,1.19679445618958,0.5130749152066766,0.4405267264292921,0.5723668172439469,0.9803764494290413

0.6064582215699709,0.409096753639446,0.9699123715007761,0.2186203639824302,0.6998185083059435,0.20228577294361297,1.1502135816930668,0.48907577334952473,1.0093726281925666,0.6018509841610441,0.4569743932890173,0.18351669841592466,0.2360415450809897

0.9048566478191873,0.17449912335248907,0.96756749382049,0.8707043013632391,0.9495156178375137,0.7414748714734604,0.657198470073042,0.9991764945876956,1.1009418288538484,0.8872212878810519,0.332628205168248,0.32692253259908655,0.28174130417295984

  • 1: Sweden - Heroes
  • 2: Russia - A Million Voices
  • 3: Italy - Grande Amore
  • 4: Belgium - Rhythm Inside
  • 5: Australia - Tonight Again
  • 6: Latvia - Love Injected
  • 7: Estonia - Goodbye To Yesterday
  • 8: Norway - A Monster Like Me
  • 9: Israel - Golden Boy
  • 10: Serbia - Beauty Never Lies
  • 11: Georgia - Warrior
  • 12: Azerbaijan - Hour Of The Wolf
  • 13: Montenegro - Adio
  • 14: Slovenia - Here For You
  • 15: Romania - De La Capat / All Over Again
  • 16: Armenia - Face The Shadow
  • 17: Albania - I'm Alive
  • 18: Lithuania - This Time
  • 19: Greece - One Last Breath
  • 20: Hungary - Wars For Nothing
  • 21: Spain - Amanecer
  • 22: Cyprus - One Thing I Should Have Done
  • 23: Poland - In The Name Of Love
  • 24: United Kingdom - Still In Love With You
  • 25: France - N'oubliez Pas
  • 26: Austria - I Am Yours
  • 27: Germany - Black Smoke
  • Occurrence of LOVE
  • Occurrence of TIME
  • Occurrence of HEART
  • Occurrence of KNOW
  • Occurrence of LET
  • Occurrence of START
  • Original language
  • Beat
  • Distance from C
  • Major/Minor key
  • Female/male lead
  • Number of lead singers
  • Range of vocabulary
  • Description:

    The visualization displays the generation of - and positioning of nodes within - a Self-Organizing Map (SOM) out of Eurovision Song Contest data.


  • The inital topic for the exploration of the subject was Shame. Based on this topic, we decided to explore the Eurovision Song Contest, a competition in which shame plays an important role. What sets apart the shamefully bad performances 'nul pointers' from the winners? With this exploration of the topic in mind we set out examining the topic, without too many expectations of what the end result might be - would we be able to find categories of bad or good performers, or even predict future winners?

  • For the data, we pursued to take apart the eurovision entries of 2015 into categorizable attributes.
  • We extracted the most common nouns and verbs of all the songs official translations in order to get some grasp of the content of the lyrics of each song, and used the frequency of these words as a metric, getting values for the prevalence of LOVE, TIME, HEART, KNOW, LET and START.

  • Original language, and whether the song had parts both in English and another language, was considered, as the multitude of languages is a distinguishing feature of the Eurovision.

  • A musical analysis tool (Serato) was used to analyze the tempo (beats-per-minute) and key of the song. The key was split into two components: Major or minor key, and the distance of the key to the note C. Distance to C was used in order to be able to represent the circular scale of notes on a finite scale 1-5, which, while not being a true representation of the key gives some indication of it in relation to the keys of other songs.

  • The amount of lead singers and the gender of the leading voice were considered, as these are often very distinguishing features of songs - is it a group, male/female solo or duet.

  • Finally, the range of vocabulary - the amount of different words used - was analysed, to give a scope of how rich the language of each songs is.

  • All metrics were mapped to a scale of 1-5, compiled into a dataset and then passed to the SOM-algorithm. The SOM is then used to plot this data into a grid of donut graphs – in which each graph shows the values of the attributes of the underlying data in that particular node. Each song is then placed into the grid into the position that best represents the values of its attributes.


    Information Visualization and Design | Aalto University

    2016
    Marija Erjavec (MA Visual Communication)
    Wolf Wikgren (MA New Media)

    Libraries:
    https://github.com/mljs/som/
    http://benpickles.github.io/peity/

    Data:
    http://www.eurovision.tv/
    Downloads:
    Full dataset
    1-5 Scaled results

    Processing:
    Excel
    Serato magic
    & manual labor

    Code