>D2< Data and Democracy Space
Research of the relations between politics and data.
Changes at "Somnien els algorismes amb ovelles polaritzades? Polarització sociopolítica i mitjans socials en línia"
Description (Castellano)
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DataPolitik2022, 2a Jornada sobre política i comunicació a l'era del big-data organitzada per l'associació Heurística i la unitat de recerca Tecnopolítica. La jornada és una invitació al diàleg transdisciplinari sobre com els entorns digitals han canviat l'estructura de la comunicació i les gramàtiques d'interacció social.
Les Jornades
La política i la comunicació han esdevingut l'era de la informació. La popularitat i la innovació en l'ús de xarxes socials com Facebook o Twitter no només ha possibilitat l'increment del nombre d'actors que poden difondre missatges polítics, comercials i de qualsevol altra naturalesa a un nombre massiu de receptors potencials, sinó que també ha produït transformacions que afecten el conjunt de l'esfera pública.
Aquestes transformacions han provocat una doble dinàmica: per una banda, els processos de desintermediació de la comunicació i autocomunicació de masses, que han trastocat el mapa d'influència tradicional dels mitjans, han anat de bracet de l'emergència de noves comunitats i pràctiques mediàtiques; de l'altra, han aparegut noves formes de mediació i de concentració de poder (econòmic, polític, social…) que s'escapen a les formes de control democràtic desenvolupades en el marc clàssic dels mitjans de comunicació de masses (marcs legals i institucionals, pràctiques d'autoregulació, etc.).
Els efectes són múltiples. Potser el més destacat aquests dies és l'increment de la polarització política i social, cosa que centrarà la primera línia de debat en aquesta edició de les Jornades Datapolitik. Un segon efecte, associat al primer, ha estat la difusió en xarxa de discursos d'odi, tot i que s'ha vist parcialment contrarestat per l'emergència de pràctiques de resposta. Els discursos d'odi i les respostes en xarxa protagonitzaran la segona línia de debat d'aquestes jornades. Finalment, una tercera línia atendrà les possibilitats obertes per plataformes alternatives de comunicació i democràcia digital per potenciar la deliberació en xarxa. En definitiva, aquestes segones jornades Datapolitik analitzen les amenaces i les possibilitats democràtiques de l'esfera pública en xarxa actual.
Entre les dificultats per avançar en el projecte de millora d'aquestes dinàmiques comunicatives en xarxa destaca la manca de socialització del coneixement científic existent al voltant dels mecanismes de producció, reproducció i consum d'informació a l'entorn digital, així com la seva relació amb els mitjans de comunicació i les maneres d'interpretació tradicionals.
La investigació científica en el camp de la difusió de la informació i de la desinformació ha avançat considerablement en els darrers anys, trencant marcs disciplinaris i generant nous corpus teòrics basats en dades.
Disciplines del camp de les ciències humanes i socials, com la psicologia social, les ciències de la comunicació, la sociologia i la politologia, s'han unit a disciplines del camp de les ciències naturals i de la computació, com la física de sistemes complexos, la teoria de xarxes, o l'aprenentatge automàtic, per aprofitar l'enorme quantitat de dades produïdes per les interaccions socials en línia, amb l'objectiu de desenvolupar un coneixement científic transdisciplinari sobre fenòmens que emergeixen en la intersecció entre les xarxes de comunicació i els processos de formació d'opinió.
Les Jornades DataPolitik són un moment de posada en comú, de construcció de línies de cooperació i de socialització per a investigadors/es, agents de la comunicació i ciutadania interessada.
Programa
Dimecres 18 de maig, de 18h a 20h al Canòdrom, Ateneu d'Innovació Digital i Democràtica
- Presentació i taula rodona: Somnien els algorismes amb ovelles polaritzades? Polarització social i política i mitjans socials en línia.
- Hi participen: Jordi Muñoz (director del Centre d'Estudis d'Opinió. Professor de ciència política, Universitat de Barcelona ), Carlos Castillo (professor de Recerca ICREA. Director del grup de recerca Web Science & Social Computing, Universitat Pompeu Fabra) i Rosa Borge Bravo (professora de Ciència Política. Directora del grup de recerca Communication Networks & Social Change (CNSC), Universitat Oberta de Catalunya)
Dijous 19 de maig, de 9h a 13h i de 16h a 18h a la Facultat de Física de la Universitat de Barcelona
- Línia 1. Polarització
- Línia 2. Discurs d'odi
- Línia 3. Deliberació
Més informació aquí
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rjsR+vGOtAFC/wDAFpqnju08UX2p38zWRDWti0g8iJwANwGOM4BPqQPpXX1keGdbfxHocOqmwnsorgloI5yN7R/wuQOmRyB6YrXoAKKKKACiiigAorF0zxHDqfibXdES3dJNIMAkkJGJPNTeMDtjpW1QAUUUUAFFZz6lOviGLTBp1w0D2zTm9A/dKwbHln/aPX6Vo0Act4r8EW/ii7sr9NT1DTNQs8iK5spdpwezAggj/Gl8JeCLPwpPf3gvb3UdS1Bla5vLxwzvt4AGAMAf56DF7xF4jh8OnSBLbvN/aWoxaemwgbGkDEMfYba2qACisXxT4jh8L6ONRngedDPFBsQgHLuFB59M1tUAFFFZmv69ZeG9JfUb8yCBXSPEa7mLOwVQPxIoA06KKKACiiigAoorFs/EcN54t1Pw+sDrLYQRTNKSNrCTOAB7YoA2qKKKACiiigAooooAKKz9d1VND0DUNWliaWOyt3naNTgsFUnA/KptMvl1PSbPUEQol1Akyqx5UMobB/OgC1RRVPVr2XTtKuryGzmvZYYy620Ay8pH8K+9AFyisg+IrSPVtL0qeOaO/wBRgeeOIr9xUALbj2IyBWvQAUUUUAFFFZ0GpTy69d6c2nXEcMESSLeMP3cpbOVX3GOfrQBo0VkT61Inie20WDTriYPA1xPdfdigXOFBPdic8Dnv0rXoAKKKxfFniOHwn4autant3njt2jBjQgE75FQdf97NAG1RWcmpTt4hl0w6dcLAlss4vSP3TMWI8sf7Q6/StGgAooooAKKKKACiiigAoqC+ulsdPubtlLLBE0pUdSFBOP0rlrDx/bX954Vt0sJ1PiG2luImLDEIRNxDeuenFAHYUUUUAFFYr+I4U8aReGjbuZpLBr4TZG0KHCbcdc85qzoWpT6vo0F9c6dcadLLu3WtyMSJhiBn6gZ+hFAGjRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRWLpPiOHVtf1zSY7d45NJkijeRiCJN6bxj0xQBtUUUUAFFZ2i6lPqtgbm4064sHErp5NwMNhWIDfQ4yPrWjQAUVi6d4jh1HxRrehJbukukrbs8pI2yeapYYHbGK2qACisFvE8Y8V3nh9LSV7i208X29SMOCxUIB65FVh4x2XHhq2utKurW41wyKIpSA1uUTcQ4oA6eiiigAooooAKKKKACis7T9SnvdQ1G2l064tktJVSOaUfLcArncnsOlQw61JceJ7rSItOuPJtYUklvW+WPe3SNf7xxyccD60Aa9FFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFfPniZ9OPj2/vYIrt/A66hAuvmEjyHuxu+bHdASm/HU/hXueuWN3qei3VjZag2nzzoUF0ke9owepAyOcZwe3WqmmeE9I0vwmnhqO1WTTvJMMiOMmXd95m9ySTmgDmPifrt1Y6doWnabJeJHq14sUkumjdOYAu5hF6MRjBHbNYuitd6X4x0j/AIR7RvFlvptw7Q6lDqiSPDtI+WUF2Yqwbr2Iroo/huv/AAiNtoM2t3Ujadci40u9CATWhX7i5yQ4GSOcZHHGBi1p/g/VW1+z1bxD4lk1V7FW+ywQ2q20SswwXYBjvOOmeB6UAc34D0OTXdZ1rW9S1fVJH07X7uGzt1umWJEV84K/xA7sYPGABVL4b6TJN8P7bxjqXiXUI9Q+yXAW4ubhngt0BdAzRkgPjG7k8mvRfDPhxPDcOpRpctP9u1Ge/JKbdhkIO3rzjHWs7TPAdpZfDf8A4Que6luLUwSQtOqhGIdmbIHIBBb9KAPJ9evbPT/Bza5oMnjC51a2Ecv9vTGaO2mO5QSyyMFKNkgKFPUCu/vbdvGXxLvtFv7u8i0jSrGGX7LbXDw+fLKSdzMhBIAGAM9aNQ+Gusa34Z/4R/WPGMs2npGqRJBYJCSVxsMh3EuBgcDbkgGtnV/B13c6zba5o+ttperx2wtZ5fswmiuIwcgNGSOQeQQcjpzQBwENzd+A7j4pXNtdzXlxZw2Jt5rlvMcbo2CbifvbdwHPULzVWVb+y0WDUdD03x1J4njEcrXV0kjw3TZBdXQuV2EZxgccV6BpHw6gtB4jGranPqx8QJGt20sYQ5VWBK46D5uAPu4HWqv/AArzWbiwt9G1DxndXOhQsg+zLaLHPIiEFUeYNkjgZIAJoAxvGMd8fFRvtf0fxDf+HXtIvsyaRM4NrLzvMkaMrE8j5ugA79uv+Hl5aXnhOM2Wu3GswRzPGJ7pCs0eDny5M8llBAyevFM1Pwlqh8QT6z4f8RPpU11EkVzDLai5ik2DCsFLLtIBxwefStDwr4Zi8L6fcwi6lvLq8uXvLu5kUKZZnxuO0cKOBgCgDGubq4HxrsLQXEotm0KWQwhzsLeco3bemcd6l+Jeq32meFUj024a1ur+9gsVuV6wiR8Fh74zz2zWrL4cSTxvb+JftLB4bB7LyNnBDOH3Zz7YxipvEnh+z8UaFcaTemRIpsFZIjh43Ugq6nsQQDQB5x4u8G23h3UPBtxYX+otE3iG0SeG6u3mWV/mxJ85OG4I4wDu6cVUutUHiTxl4hGsWHii+stOuvsVnb6RvWKIqPmdijKS5JyM9BXVTfD/AFjU7/SLrXPF0t+NKvIrqCNLJIVYoed+GO5j03cAc8c1cvfBWoQ6/fax4b8QtpEuoBTeQyWi3MUjqMBwpK7Wx15wfSgDz/WZdevPhVfWGpLqUDQ63BDp9zqUW2doDKnls+fvMpJBPfFdHr2jnwFe+H9X0nU9Tke41OGxv4rq8eZbtJcgsQxIDg8jbitW6+GkF54Lm8Pz6xeSS3V4t7dX74Mkkm4McDOFHGAB096mg8Eajdavp134i8Sy6vb6ZJ51nbfZEhHmgYWSQqTvYA8cAZ5xQBzOtvo2o+KtXiv7rxJ4huIpAkdno0cyRaeAPulkcIXzySx9sDFc1ftPr3wRim1O5v5Z7HWBbRtNOwkKfaFUCTBwzAHGTnBHFejw+BdW0zUtVk0PxS+n2Gp3b3k9ubJJZElf75jkJ+XOB1U4qGP4X28PgO+8Kx6tceXNeG7gumjDSQnerqDzh8FeTxnPagDI8ZaTeadrGmpcad4g1fwlb2JjMGm3cjTJcbyd8gDB5Btxjnjn8eh+G17p91ol3Hp2uXupQRXTARX6sJ7MEDELbvmOOcE/0ouPBuuNeWeq2niySDWY7b7LdTtZK8Nym4sCYdwCsM9Qa0/C3hb/AIR46hdXN/JqGp6lMJru6eMRhyBtUKg4VQO3P1oA5z4kW2qyalpM50/VtS8OxrJ9us9JnaOZnONjEKQzqOeAetc6viu30P4eeKrzw5rWoTS2zwrDY6ojefprSMqYJfJYZJYZyBjHPNeg+IvC95qmq2Wr6TrUulalaxtDv8kTRSxsQSrxkjPIyCCDVC1+HdvPba7/AMJBfyatea3GkV1OIhAqog+QIgztwecknkCgDnfFnhp/AnhKTxPpWs6o+r6cY5Z5bm9kkS9BdVdZEYlcHJxgDHFC+HoPFHxe8Qfa7q8isU0+zaS2t52hMzMG27mUhsDB4z1I9K2H+HuqalbW2ma/4sn1LRbd0b7H9jSJ5whyqyyAkuBgZwBnHrVrUfA+oSeLrzxLo/iOTTr25hjgMbWqzRFFBzuUkZPQggjGD1zQBxGs6jqei+E/iL4ej1O8mTRTayWV1JMTNHHNtbZv6nbggHrg1d8U2t34J8M2f2HVNauNR8Q39tbXlwsxllXIZnMCnhXPIAHt0xXSv8N4ZvCGtaPcarPPf604lvdSkjG53BGMICAFAGAueK3PEnhe18TaEmm3E0sLwuk1vcwnEkEqfddfcfyJoA88083Wk+J9Fk8NaN4wgt5rlYNTi1NZHheJuDKS7NtZTg5GOM16T4rkkh8H63LE7JIlhOyupwVIjbBB7GsS08G6xPrNhf8AiLxTLqiaexkt7eG0W1QyYxvk2sd5HYcD2rZ8X/8AIla9/wBg64/9FtQB5r/wjlxafCaDxcmu6qfEUGmx6gt2145UgIH8ox52Fdvy9Mk8knNaUU03xC8Zrp1/c3dtpFppNtePZ207Q+fLMN3zspDFVHGM9ag8L+BtT1v4e6HY3nim5bQLmygllsFtlEjKVVjH52c7M9sZxxmus1nwZLc63b65oOqto2pxW/2V3Fus0U0IOQrRkjoehBBFAHE6q9zoUHjzwl9tubvTY9Be+tPtMpke3DKytHvPJGRkZ6Va1W50/wDsTwdZ6lq+p+Q+mRt/Y2lRSme8PlrhmaM7gi88cZPfiujg+HwOl+IF1DV5r3Vtdtzb3N+8SrsTaVVUjBwqjOcZ57mm3XgK6jv9I1PRddNhqWn6cumtLJaCeOeEYIBQsMHIzkGgDlPC1/NaeIvFWlWUet2WmLo/2u3tNVkYyQv8ylkyzMqn0JzkVUsNHuLb4MXXi2bW9Wn1efRm+d7x9iLxt2qOhAA565JPeu307wBNaa7qWsXevXF9d6lp5s7gywqoBzwyAcKoHG3n1zk1dHguMfDf/hDvtreX9i+yfafL5xj723P6ZoA4q70S21H4leCprie9MlxpLyyFLuRfmRI8YweAe4HXvmpPGuh2Z1dNC0C51aXxJqRMv/IVuPKsoifmmdQ+AB0Ve5/I9Xqvgm4u77w/qGm60+n3ujwm3En2ZZVmjYKGBUnjO3r2zWXp3w817SNR1K/svGbLc6jN5txLJpkcjt6LuLfdA4AHAoAreKLSw0Kw8OaHqHiPWZLdFcPY2ayyXmpsB1LodwUEkkdDnGeBWR4Z1l9D8aa5a2FprdppMegtqUdhq7szCRHxuQMzMqkccnOQfautvfBGrXN9pesReJzHr1jFJA149gjRzxO2drRBgBjjkGpNJ8CS2fiybxFqOtzand3Ni1lcpLAqRspYMNij7qjbjHOckk80Ac5oHg648R+CrLxFN4j1SHxHewrdrfi6fy4C3zBBFkJsA4K49aNW8Q6loPibxtdi5ad7DQreaJDnyhLhhuCZIHOCfbvWl/wrXUI9Jfw7B4suY/DLkqbH7KhmWInJiE+c7eSPuk44zW1F4F05NX1W5c77LUdPi05rPZhUiQFeGznoce1AHH6h4Ul0r4eP4qt9e1b/AISO3sv7Qe9e8dklYLvZDGTs2HkAY9K9L0W/bVdB07UWQI13bRzlB/CWUNj9a4s/DjVJ9ITw/d+MLqbw6m1PsgtEWdol6RtMDkrwBwoOOK37m01KLxdoiafLNFpENtKtzbqgEXAAj567sngDsDQAvj3Wrjw74F1jVbPH2m3tyYiRnaxIUHHsTn8K828f+CI9L+F0upR6vqc19i2e9knvHkS73SpnKMSowxBGAOmO9ewapptrrGlXWm3sfmWt1E0Uq5xlSMH6GuC1D4Y6vq2groN/4zuZtKg2fZ4vsSCT5CNokcH94AB6LzgnOKALF1capL8VdbsbC7dJP+EbV7ZHcmNJjIwVtvTrjnHSuJ0ue10i40oa9L4q8N+IEnjFzqF5JJcWl6+fmQncU2t9Bj14zXqV14Pt73xPqGsT3MhS+0v+zZIFG3C7iSwYHIPP4Vgv8OdVvdLt9C1bxbLfaBC0ebU2SJLKiEFEeXccgbRkhQTjrQBBFYf8J1488S22rXl8umaO8NtbWVtcvApZk3NI+wgsc9OeBUGr2eq+G18IadJr9zfo3iRY0lZiJPIKuVikbP7wj1PXjjiui1Pwdff8JFc674d15tIu72NEvUe1W4in2DCNtJGGA4yD07VRm+GVu3hyOxi1e6j1VNR/tX+1Sis7XfdynQrg429MAUATeIbu4i+K3gu2juJUgmhvzLErkK+I1xuHQ47Zrm/Aug3mtjVdduNZ1KS+s9UvIbCJrphBGAxwGX+Ibm5z2AHQV0tj4Gvx4r03xJrHiOXUr6xSWNVFqsMWx1xhVBODySSSc8dMVqaB4Tg0TRtR0x7h7mG+ubieQ7dhAlOSowe2etAHk1nNFowsj4mm8VeHfEUc6GfWLiSS4s7ht3KnDFNhHGMADjk4r3eSQRwvJgsFUtx3rz9/hvqt1oyeHb7xfPc+HV2qbU2SCdolIKxmbPTgc7QeK9CVVRAigBVGAB2FAHj+i+H5fF/w6uPFl9rGpLrd9DcTxSR3brFbqCwWIRg7SmAAQQc5NdP4DsLFvh74V1ee28y60/TSYHycoGQbwB0OQo61Efhxf21neaPpfim4sfD10zlrAWqO8QckukcpOVUknjBIyee9dX4c0VfD3hvT9GWYzrZwLCJGXbvwOuO1AHnvhXwvJ428HxeJtU1rVE1vUBJNDPb3skaWfzEIqIp24GBnIOeaoaX4h1Px7aeB9Lvb24tYdQtrm41F7WQxPc+SxjChlwQGILED17V00fw81TTrS50nQ/Fs+naFOzkWf2NJJIFckssUpIKjk4yDjPrzV6++H1n/AGXolvol5LpV5ogIsLtEEhUMMOHU8OG6npzQBz+k+H4/D3xuht7a7uprN9BkaGK5maUwfvkyqsxLbe+CTyTW38I7q4vfhhpFxd3EtxO5n3SSuXZsTyAZJ56ACpdF8E3tj4wPifVPEEup37WbWbL9mWKNVLKw2KCdoGDxzkknNVR4W1Twx4C0nQdB1K5a5tr5CZo4QPMjeZmcNkkKoVjk/wCyMcmgDu68k8HeFP8AhLNJ1a+1fWdXeYaldQ2RhvpI/sgWQgFQpALZz97PAA7V63XjvgTw7ruoaRrUmleKptMtrnVrtJofsqzEESEbo2JBQkfXpmgCkdX1nxR4c8ARTardW1zeahcWV5cWshRpkQOhPHGSq9exORW7Nogl8baf4Bj1PU49EtNMfU5x9sfzblmmKLG0md2xeuARXSr4BsLaLwvBYzvBbaBK0kSFdxlJUg7jxgkkknHU1P4j8JSavqtlrWmapJpWs2aNElysQlV4m5KOhI3DPI5GDQByg+0eEvF2q+GrO/u5tKutClv7eO4naV7SVCVIR2JbaRzyetZeneGZ3+EUXip9e1Y+IItNN9DeG9k2oETcsezOwrgAHIJJJJNdavhGTTLfXte1XVZNV1m50+S3+0NCIUihCk7EQE4GeTycn8a5jwZ4K1XWvhrpFlL4quY9BvLVGmsVtk80q3LRrNnIQnPG0nBxnFAFnW9asNbj8Mz6xqWqul7paXZ0DR4pfNndwD5jtGd2wZIAOOec9aydH8S3nhxPHi2MWrQWen6fFdWNnq7F5Ld2VhnlmIUnBwT27V3epeCLj/hIrfXPDusDSLqOyFg8b2guInhU5UBSykEeuew/GpB4HXRZfEWs6he3mvPqWnmO9tmiUPOVB4jAIAyp2hfpzQByvijwpLpHwquPENr4g1ga39kSe4uzfSET7tu5SudoHzHbgAjA5rY8W3OmTa3plpquqaxeR/YA40LSIpjLIxP+ukeIg7ewBxzznrXC65NZat4Dj0HSPGmoaqZxHDYaCYEFwjbhhJmA3FUGeuB8o5OBXqt94Jvx4jGvaHrw028ktEtLlZbQXEcqp90gFlKkfX8KAOH0fU7y30T4m6dbtrFpaafp6zWMGoyk3FsXgkJw24kDKggZyPrmjW9HuNE+Ftj42h1vVn1+GG0uWne8co4dowYzHnbsw/THOOc812Fp8Nzbp4o87Xbm7m8RWgt7qaaJdyuFdd4xgYw/C44AAzWnrPgyPWPh6vhJr1oo1t4IPtIjyf3RQ52577PXvQBg3VofGfxL1jSNRvLyPStFtbcpaW1w8ImllBbexQgnAGAM4/Wsfw/bP4evviXBJ4ge1+ztb7dUuh5zwqYcqTyN7KCB6kgdTXZ614QurrxCuv6FrTaRqbQC3uGNuJ4p4wcruQkfMD0YH2rKi+FsEmkeJbDUtZur5tfMUk87Iqukic7hjjG4AhcAAAD3oA4HVr2z0rTdO1jw8njAXsd1b+Zq160ywXSs4DbxI2GDZ4CrXv1ee6t8O9b8RaVHYa34xluEgdJIPIsEhXepBDSDcS/GeAVGTnHFehUAcT8K7q4vPBzy3VxLPJ9vul3yuWOBKwAyewFUdUt38XfE650C+u7uLSNM0+Oc21tcND9olkY/MzIQSoA6Z611HhPw4nhbRTpyXLXANxLPvZNv33LYxk9M4qlr3hG4v9eg1/RtXfSdWjgNtJL5AnjmizuCuhIzg8ggg0AefW81z4E1L4oXNtdzXktnaWL20l0/mOuUkCBieW25HXqAM1SYX9voMGpaNp/jqTxSqpN9suEkeG5fgsroXK+WecADjivQtH+HkVnJ4jk1fVJtXbX4o47wyxiP7qsp27egw/AH3do61T/4V3rM2mwaJeeM7ubQYiq/ZltFjneNSCsbTg5xwOQoJoApmeST4o61cFHglbwrG5U8Mjb2OPqK5pLW68Q6V8KIJdSu4ZrkXBluklPnECLLYc8glQRnqM16fJ4SifxPfa0t0ym60wad5IThAGJ3Zzz16ViT/DPfpHhiyt9duLWbw+HMFzFCu52K4BIJIwDjI5yMjvQBRMZ8A+P9NsNPur2bSdVsrqSSzuLh5hFJAofehckjcDgjOP0rj9JupvEXhw63f2njafX7sPNBfWCyC3gOTsWJQ4UoMDOQc816jo3g+5t9fbXte1ltY1IQG2gItlgigjJywVATye5J6cVlR/DvVtPsbjR9E8X3Gn6FMz7bQ2aSSQK5JZI5SwKjk4yCR9aAOf1STXfEl98OdP1S51DSbjUbe9XU44HMLvsRCQR2ztP0DHFXPEdno2k6npehXmsa/fWkFmxj0Sw8+W4mJc/vZZI23FQPlAOMY4NdaPBVrDqvhe7trmVIvD8U8UUTjeZhIgTLMT1GM++ag1bwdfzeK28R6Hrv9mXs1sLW5WW0FxHKgOVIBZSpHrn8KAOB0bxNfeHdP+IS2aarDbaXbW8+n2urN5kts0iNnOWY7cgMAT0+prp7DwDKuk6Zqtp4k1OHXv3U899cXMk0c+cF0aIsF2HJAAxjjmtDSvh3DZ3mvz6jqlxqo163SG9FwiqWKhhlSuAow2AAOMDmqg+HOo3Nja6Lqviue+8PWzoRYtaIkkqIQUSSUH5lGB0UE4oA53V/E2raNb/EWezu5PtEeo2ttatIxZbfzFRSQDwMbifrVzxf4f8A+FfeGP8AhKdI1bVX1HT5IWuTdXskq3ys6oyyKxK87sjAGK6iXwBp94niiG/mee21+VJJEC7TCVUAFTzkggMDjqKot4A1XU1s7PxF4rm1TSbWRJRaCzSFpyhyolcElwOM8DPegDtrqcWtnNcFSwijZ9o6nAzivCdIupvEfhw63f2njafXrsPLBe6esgt7c5OxYlDhSgwM5BzzXvZAIIIBB6g1wEfw71bTrG40jQ/F8+n6FMzlbQ2aSyQK5JZY5SwKjk4yCR9aAMG/uNf1/UPhvZandahpN1qEN6upRwOYXYpGpOQOhO089RuOMVsaBZN4Y+LM/h+xvLx9JudF+3fZ7m4eYRzCYJlSxJAIPPv+Fbw8FWsWqeF7u2uZUi8PxTxRRON5mEkYTLMT1GM++e1XD4cQ+Ol8T/aW3rpp0/7Ps4wZBJu3Z9sYxQAvi3Rn1zw5dWkOoTadcKPNgu4pShikXkEkdV9R6Zrg/hxruofEPWW1vUrxYY9HjW2SwtpiFlmZctO4GMqf4Acjr3HPeeKtAl8TaI+kjUJLK3ndRctEmXki/ijBz8u7oTzxnjmqTeCrW38S6drOkzf2eba2+xz28ceY7mAD5UYZGCvZv6UAeb30mk6jb6tci88V+ItUWSYx6lpizQ21qRnaqfOIwq4GTznBNWLi91bxJo3wyik1e8t5NUEqXk1vKUeVRF82SO5APPYnI5rp9P8AhxqWm6M/h228WTx+HWMirbJZoJ1jcklPOJPHJ52556irunfD9LC38JxHUnkPh1pSjeSB54dSuDz8uAffpQBgeL7R/hppml+ItI1C7mi09/stxY3l4z/bIpGJAGc/OpOQQOg9BUti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2a Jornada sobre política i comunicació a l'era del big-data organitzada per l'associació Heurística i la unitat de recerca Tecnopolítica. La jornada és una invitació al diàleg transdisciplinari sobre com els entorns digitals han canviat l'estructura de la comunicació i les gramàtiques d'interacció social.</p><h4><strong>Les Jornades</strong></h4><p>La política i la comunicació han esdevingut l'era de la informació. La popularitat i la innovació en l'ús de xarxes socials com Facebook o Twitter no només ha possibilitat l'increment del nombre d'actors que poden difondre missatges polítics, comercials i de qualsevol altra naturalesa a un nombre massiu de receptors potencials, sinó que també ha produït transformacions que afecten el conjunt de l'esfera pública.</p><p>Aquestes transformacions han provocat una doble dinàmica: per una banda, els processos de desintermediació de la comunicació i autocomunicació de masses, que han trastocat el mapa d'influència tradicional dels mitjans, han anat de bracet de l'emergència de noves comunitats i pràctiques mediàtiques; de l'altra, han aparegut noves formes de mediació i de concentració de poder (econòmic, polític, social…) que s'escapen a les formes de control democràtic desenvolupades en el marc clàssic dels mitjans de comunicació de masses (marcs legals i institucionals, pràctiques d'autoregulació, etc.).</p><p>Els efectes són múltiples. Potser el més destacat aquests dies és<strong> l'increment de la polarització política i social</strong>, cosa que centrarà la primera línia de debat en aquesta edició de les Jornades Datapolitik. Un segon efecte, associat al primer, ha estat la difusió en xarxa de discursos d'odi, tot i que s'ha vist parcialment contrarestat per l'emergència de pràctiques de resposta.<strong> Els discursos d'odi i les respostes en xarxa</strong> protagonitzaran la segona línia de debat d'aquestes jornades. Finalment, una tercera línia atendrà les possibilitats obertes per plataformes alternatives de comunicació i democràcia digital per potenciar la<strong> deliberació en xarxa</strong>. En definitiva, aquestes segones jornades Datapolitik analitzen les amenaces i les possibilitats democràtiques de l'esfera pública en xarxa actual. </p><p>Entre les dificultats per avançar en el projecte de millora d'aquestes dinàmiques comunicatives en xarxa destaca la <strong>manca de socialització del coneixement científic </strong>existent al voltant dels mecanismes de producció, reproducció i consum d'informació a l'entorn digital, així com la seva relació amb els mitjans de comunicació i les maneres d'interpretació tradicionals. </p><p>La investigació científica en el camp de la difusió de la informació i de la desinformació ha avançat considerablement en els darrers anys, trencant marcs disciplinaris i generant nous corpus teòrics basats en dades. </p><p>Disciplines del camp de les ciències humanes i socials, com la psicologia social, les ciències de la comunicació, la sociologia i la politologia, s'han unit a disciplines del camp de les ciències naturals i de la computació, com la física de sistemes complexos, la teoria de xarxes, o l'aprenentatge automàtic, per aprofitar l'enorme quantitat de dades produïdes per les interaccions socials en línia, amb l'objectiu de desenvolupar un <strong>coneixement científic transdisciplinari</strong> sobre fenòmens que emergeixen en la intersecció entre les xarxes de comunicació i els processos de formació d'opinió.</p><p>Les Jornades DataPolitik són un moment de posada en comú, de construcció de línies de cooperació i de socialització per a investigadors/es, agents de la comunicació i ciutadania interessada. </p><h4><strong>Programa</strong></h4><h5><strong>Dimecres 18 de maig, de 18h a 20h al Canòdrom, Ateneu d'Innovació Digital i Democràtica</strong></h5><ul><li>Presentació i taula rodona: <em>Somnien els algorismes amb ovelles polaritzades? Polarització social i política i mitjans socials en línia</em>.</li><li>Hi participen: <strong>Jordi Muñoz</strong> (director del Centre d'Estudis d'Opinió. Professor de ciència política, Universitat de Barcelona ), <strong>Carlos</strong> <strong>Castillo</strong> (professor de Recerca ICREA. Director del grup de recerca Web Science & Social Computing, Universitat Pompeu Fabra) i<strong> Rosa Borge Bravo </strong>(professora de Ciència Política. Directora del grup de recerca Communication Networks & Social Change (CNSC), Universitat Oberta de Catalunya<strong>)</strong></li></ul><h5><strong>Dijous 19 de maig, de 9h a 13h i de 16h a 18h a la Facultat de Física de la Universitat de Barcelona</strong></h5><ul><li>Línia 1. Polarització</li><li>Línia 2. Discurs d'odi</li><li>Línia 3. Deliberació</li></ul><p>Més informació <a href="https://heuristica.participa.cloud/conferences/DataPolitik2022?locale=ca" target="_blank">aquí</a></p>
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- Hi participen: Jordi Muñoz (director del Centre d'Estudis d'Opinió. Professor de ciència política, Universitat de Barcelona ), Carlos Castillo (professor de Recerca ICREA. Director del grup de recerca Web Science & Social Computing, Universitat Pompeu Fabra) i Rosa Borge Bravo (professora de Ciència Política. Directora del grup de recerca Communication Networks & Social Change (CNSC), Universitat Oberta de Catalunya)
Dijous 19 de maig, de 9h a 13h i de 16h a 18h a la Facultat de Física de la Universitat de Barcelona
- Línia 1. Polarització
- Línia 2. Discurs d'odi
- Línia 3. Deliberació
Més informació aquí
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+
DataPolitik2022, 2a Jornada sobre política i comunicació a l'era del big-data organitzada per l'associació Heurística i la unitat de recerca Tecnopolítica. La jornada és una invitació al diàleg transdisciplinari sobre com els entorns digitals han canviat l'estructura de la comunicació i les gramàtiques d'interacció social.
Les Jornades
La política i la comunicació han esdevingut l'era de la informació. La popularitat i la innovació en l'ús de xarxes socials com Facebook o Twitter no només ha possibilitat l'increment del nombre d'actors que poden difondre missatges polítics, comercials i de qualsevol altra naturalesa a un nombre massiu de receptors potencials, sinó que també ha produït transformacions que afecten el conjunt de l'esfera pública.
Aquestes transformacions han provocat una doble dinàmica: per una banda, els processos de desintermediació de la comunicació i autocomunicació de masses, que han trastocat el mapa d'influència tradicional dels mitjans, han anat de bracet de l'emergència de noves comunitats i pràctiques mediàtiques; de l'altra, han aparegut noves formes de mediació i de concentració de poder (econòmic, polític, social…) que s'escapen a les formes de control democràtic desenvolupades en el marc clàssic dels mitjans de comunicació de masses (marcs legals i institucionals, pràctiques d'autoregulació, etc.).
Els efectes són múltiples. Potser el més destacat aquests dies és l'increment de la polarització política i social, cosa que centrarà la primera línia de debat en aquesta edició de les Jornades Datapolitik. Un segon efecte, associat al primer, ha estat la difusió en xarxa de discursos d'odi, tot i que s'ha vist parcialment contrarestat per l'emergència de pràctiques de resposta. Els discursos d'odi i les respostes en xarxa protagonitzaran la segona línia de debat d'aquestes jornades. Finalment, una tercera línia atendrà les possibilitats obertes per plataformes alternatives de comunicació i democràcia digital per potenciar la deliberació en xarxa. En definitiva, aquestes segones jornades Datapolitik analitzen les amenaces i les possibilitats democràtiques de l'esfera pública en xarxa actual.
Entre les dificultats per avançar en el projecte de millora d'aquestes dinàmiques comunicatives en xarxa destaca la manca de socialització del coneixement científic existent al voltant dels mecanismes de producció, reproducció i consum d'informació a l'entorn digital, així com la seva relació amb els mitjans de comunicació i les maneres d'interpretació tradicionals.
La investigació científica en el camp de la difusió de la informació i de la desinformació ha avançat considerablement en els darrers anys, trencant marcs disciplinaris i generant nous corpus teòrics basats en dades.
Disciplines del camp de les ciències humanes i socials, com la psicologia social, les ciències de la comunicació, la sociologia i la politologia, s'han unit a disciplines del camp de les ciències naturals i de la computació, com la física de sistemes complexos, la teoria de xarxes, o l'aprenentatge automàtic, per aprofitar l'enorme quantitat de dades produïdes per les interaccions socials en línia, amb l'objectiu de desenvolupar un coneixement científic transdisciplinari sobre fenòmens que emergeixen en la intersecció entre les xarxes de comunicació i els processos de formació d'opinió.
Les Jornades DataPolitik són un moment de posada en comú, de construcció de línies de cooperació i de socialització per a investigadors/es, agents de la comunicació i ciutadania interessada.
Programa
Dimecres 18 de maig, de 18h a 20h al Canòdrom, Ateneu d'Innovació Digital i Democràtica
- Presentació i taula rodona: Somnien els algorismes amb ovelles polaritzades? Polarització social i política i mitjans socials en línia.
- Hi participen: Jordi Muñoz (director del Centre d'Estudis d'Opinió. Professor de ciència política, Universitat de Barcelona ), Carlos Castillo (professor de Recerca ICREA. Director del grup de recerca Web Science & Social Computing, Universitat Pompeu Fabra) i Rosa Borge Bravo (professora de Ciència Política. Directora del grup de recerca Communication Networks & Social Change (CNSC), Universitat Oberta de Catalunya)
Dijous 19 de maig, de 9h a 13h i de 16h a 18h a la Facultat de Física de la Universitat de Barcelona
- Línia 1. Polarització
- Línia 2. Discurs d'odi
- Línia 3. Deliberació
Més informació aquí
-<p><br></p>
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2a Jornada sobre política i comunicació a l'era del big-data organitzada per l'associació Heurística i la unitat de recerca Tecnopolítica. La jornada és una invitació al diàleg transdisciplinari sobre com els entorns digitals han canviat l'estructura de la comunicació i les gramàtiques d'interacció social.</p><h4><strong>Les Jornades</strong></h4><p>La política i la comunicació han esdevingut l'era de la informació. La popularitat i la innovació en l'ús de xarxes socials com Facebook o Twitter no només ha possibilitat l'increment del nombre d'actors que poden difondre missatges polítics, comercials i de qualsevol altra naturalesa a un nombre massiu de receptors potencials, sinó que també ha produït transformacions que afecten el conjunt de l'esfera pública.</p><p>Aquestes transformacions han provocat una doble dinàmica: per una banda, els processos de desintermediació de la comunicació i autocomunicació de masses, que han trastocat el mapa d'influència tradicional dels mitjans, han anat de bracet de l'emergència de noves comunitats i pràctiques mediàtiques; de l'altra, han aparegut noves formes de mediació i de concentració de poder (econòmic, polític, social…) que s'escapen a les formes de control democràtic desenvolupades en el marc clàssic dels mitjans de comunicació de masses (marcs legals i institucionals, pràctiques d'autoregulació, etc.).</p><p>Els efectes són múltiples. Potser el més destacat aquests dies és<strong> l'increment de la polarització política i social</strong>, cosa que centrarà la primera línia de debat en aquesta edició de les Jornades Datapolitik. Un segon efecte, associat al primer, ha estat la difusió en xarxa de discursos d'odi, tot i que s'ha vist parcialment contrarestat per l'emergència de pràctiques de resposta.<strong> Els discursos d'odi i les respostes en xarxa</strong> protagonitzaran la segona línia de debat d'aquestes jornades. Finalment, una tercera línia atendrà les possibilitats obertes per plataformes alternatives de comunicació i democràcia digital per potenciar la<strong> deliberació en xarxa</strong>. En definitiva, aquestes segones jornades Datapolitik analitzen les amenaces i les possibilitats democràtiques de l'esfera pública en xarxa actual. </p><p>Entre les dificultats per avançar en el projecte de millora d'aquestes dinàmiques comunicatives en xarxa destaca la <strong>manca de socialització del coneixement científic </strong>existent al voltant dels mecanismes de producció, reproducció i consum d'informació a l'entorn digital, així com la seva relació amb els mitjans de comunicació i les maneres d'interpretació tradicionals. </p><p>La investigació científica en el camp de la difusió de la informació i de la desinformació ha avançat considerablement en els darrers anys, trencant marcs disciplinaris i generant nous corpus teòrics basats en dades. </p><p>Disciplines del camp de les ciències humanes i socials, com la psicologia social, les ciències de la comunicació, la sociologia i la politologia, s'han unit a disciplines del camp de les ciències naturals i de la computació, com la física de sistemes complexos, la teoria de xarxes, o l'aprenentatge automàtic, per aprofitar l'enorme quantitat de dades produïdes per les interaccions socials en línia, amb l'objectiu de desenvolupar un <strong>coneixement científic transdisciplinari</strong> sobre fenòmens que emergeixen en la intersecció entre les xarxes de comunicació i els processos de formació d'opinió.</p><p>Les Jornades DataPolitik són un moment de posada en comú, de construcció de línies de cooperació i de socialització per a investigadors/es, agents de la comunicació i ciutadania interessada. </p><h4><strong>Programa</strong></h4><h5><strong>Dimecres 18 de maig, de 18h a 20h al Canòdrom, Ateneu d'Innovació Digital i Democràtica</strong></h5><ul><li>Presentació i taula rodona: <em>Somnien els algorismes amb ovelles polaritzades? Polarització social i política i mitjans socials en línia</em>.</li><li>Hi participen: <strong>Jordi Muñoz</strong> (director del Centre d'Estudis d'Opinió. Professor de ciència política, Universitat de Barcelona ), <strong>Carlos</strong> <strong>Castillo</strong> (professor de Recerca ICREA. Director del grup de recerca Web Science & Social Computing, Universitat Pompeu Fabra) i<strong> Rosa Borge Bravo </strong>(professora de Ciència Política. Directora del grup de recerca Communication Networks & Social Change (CNSC), Universitat Oberta de Catalunya<strong>)</strong></li></ul><h5><strong>Dijous 19 de maig, de 9h a 13h i de 16h a 18h a la Facultat de Física de la Universitat de Barcelona</strong></h5><ul><li>Línia 1. Polarització</li><li>Línia 2. Discurs d'odi</li><li>Línia 3. Deliberació</li></ul><p>Més informació <a href="https://heuristica.participa.cloud/conferences/DataPolitik2022?locale=ca" target="_blank">aquí</a></p>