Twitter, d\u00fcnya \u00e7ap\u0131nda milyonlarca kullan\u0131c\u0131n\u0131n muazzam miktarda veri \u00fcretti\u011fi, her yerde bulunan bir platform haline geldi. Ara\u015ft\u0131rmac\u0131lar, bu verilerin k\u00fcresel \u00e7apta insan faaliyetlerine dair de\u011ferli bilgiler sa\u011flayabilece\u011fini ke\u015ffettiler.<\/p>\n\n
Twitter’\u0131n a\u00e7\u0131k API’s\u0131, ara\u015ft\u0131rmac\u0131lar\u0131n tweetlerin co\u011frafi konumlar\u0131 da dahil olmak \u00fczere ham tweet verilerine eri\u015fmelerine ve bunlar\u0131 analiz etmelerine olanak tan\u0131r. Bu, tweet yo\u011funlu\u011funa dayal\u0131 insan faaliyeti modellerini ortaya \u00e7\u0131karan karma\u015f\u0131k haritalar\u0131n olu\u015fturulmas\u0131n\u0131 sa\u011flam\u0131\u015ft\u0131r.<\/p>\n\n
Twitter’daki en yayg\u0131n dil \u0130ngilizcedir, ancak \u00e7ok \u00e7e\u015fitli ba\u015fka diller de temsil edilmektedir. Ara\u015ft\u0131rmac\u0131lar, d\u00fcnya \u00e7ap\u0131nda farkl\u0131 dillerin da\u011f\u0131l\u0131m\u0131n\u0131 g\u00f6steren haritalar olu\u015fturarak Twitter kullan\u0131c\u0131 taban\u0131n\u0131n dilsel \u00e7e\u015fitlili\u011fini ortaya koymu\u015flard\u0131r.<\/p>\n\n
Tweetlerin co\u011frafi da\u011f\u0131l\u0131m\u0131, \u00f6zellikle geli\u015fmi\u015f b\u00f6lgelerde, elektriklenme ve yapay \u0131\u015f\u0131k kullan\u0131m oranlar\u0131yla yak\u0131ndan \u00f6rt\u00fc\u015fmektedir. Bu, Twitter kullan\u0131m\u0131n\u0131n teknolojiye eri\u015fimden b\u00fcy\u00fck \u00f6l\u00e7\u00fcde etkilendi\u011fini d\u00fc\u015f\u00fcnd\u00fcrmektedir.<\/p>\n\n
Ara\u015ft\u0131rmac\u0131lar ayr\u0131ca Twitter’da retweetleme ve at\u0131flar\u0131n co\u011frafyas\u0131n\u0131 da analiz ettiler. Birbirlerini retweetleyen veya at\u0131fta bulunan kullan\u0131c\u0131lar aras\u0131ndaki ortalama mesafenin \u015fa\u015f\u0131rt\u0131c\u0131 derecede b\u00fcy\u00fck oldu\u011funu ke\u015ffettiler. Bu, Twitter’\u0131n birbirinden uzakta ya\u015fayan insanlar\u0131 birbirine ba\u011flamak i\u00e7in kullan\u0131ld\u0131\u011f\u0131n\u0131 g\u00f6stermektedir.<\/p>\n\n
Ara\u015ft\u0131rmac\u0131lar, farkl\u0131 \u00fclkelerdeki tweet say\u0131s\u0131na k\u0131yasla ana ak\u0131m haber kapsam\u0131 oran\u0131n\u0131 kar\u015f\u0131la\u015ft\u0131rd\u0131lar. Avrupa ve ABD’nin orant\u0131s\u0131z bir medya kapsam\u0131 ald\u0131\u011f\u0131n\u0131, Latin Amerika ve Endonezya’n\u0131n ise g\u00f6z ard\u0131 edildi\u011fini buldular.<\/p>\n\n
Twitter h\u0131zla b\u00fcy\u00fcmeye devam etmektedir ve daha fazla veri kullan\u0131labilir hale geldik\u00e7e, ara\u015ft\u0131rmac\u0131lar daha da ayr\u0131nt\u0131l\u0131 analizler yapabileceklerdir. Bu veriler, insan davran\u0131\u015flar\u0131, demografi ve ileti\u015fim kal\u0131plar\u0131 hakk\u0131nda de\u011ferli bilgiler sa\u011flayabilir.<\/p>\n\n
\u00d6nemli bir ara\u015ft\u0131rma projesi olan Global Twitter Heartbeat, Sandy Kas\u0131rgas\u0131 s\u0131ras\u0131nda ifade edilen olumlu ve olumsuz duygular\u0131n ve ba\u015fkan adaylar\u0131na verilen deste\u011fin haritalar\u0131n\u0131 olu\u015fturmak i\u00e7in ABD’den bir milyardan fazla tweeti analiz etti.<\/p>\n\n
Bu \u00e7al\u0131\u015fmalarda analiz edilen verilerin, g\u00f6nderilen t\u00fcm tweetlerin yaln\u0131zca k\u00fc\u00e7\u00fck bir k\u0131sm\u0131n\u0131 temsil etti\u011fini belirtmek \u00f6nemlidir. Ayr\u0131ca, co\u011frafi etiketlemeyi etkinle\u015ftiren kullan\u0131c\u0131lar, di\u011fer kullan\u0131c\u0131lardan farkl\u0131 davranabilirler. Bu nedenle, sonu\u00e7lar t\u00fcm Twitter kal\u0131plar\u0131n\u0131 tam olarak temsil etmeyebilir.<\/p>","protected":false},"excerpt":{"rendered":"
Twitter: \u0130nsan Faaliyetlerinin K\u00fcresel Haritas\u0131 Twitter, d\u00fcnya \u00e7ap\u0131nda milyonlarca kullan\u0131c\u0131n\u0131n muazzam miktarda veri \u00fcretti\u011fi, her yerde bulunan bir platform haline geldi. Ara\u015ft\u0131rmac\u0131lar, bu verilerin k\u00fcresel \u00e7apta insan faaliyetlerine dair de\u011ferli…<\/p>\n","protected":false},"author":6,"featured_media":0,"comment_status":"closed","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[3462],"tags":[1683,3460,3461,171,3459,385],"class_list":["post-1575","post","type-post","status-publish","format-standard","hentry","category-data-science","tag-digital-humanities","tag-human-activity","tag-language-diversity","tag-social-media","tag-twitter","tag-data-analysis"],"_links":{"self":[{"href":"https:\/\/www.lifescienceart.com\/tr\/wp-json\/wp\/v2\/posts\/1575","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.lifescienceart.com\/tr\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.lifescienceart.com\/tr\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.lifescienceart.com\/tr\/wp-json\/wp\/v2\/users\/6"}],"replies":[{"embeddable":true,"href":"https:\/\/www.lifescienceart.com\/tr\/wp-json\/wp\/v2\/comments?post=1575"}],"version-history":[{"count":1,"href":"https:\/\/www.lifescienceart.com\/tr\/wp-json\/wp\/v2\/posts\/1575\/revisions"}],"predecessor-version":[{"id":1576,"href":"https:\/\/www.lifescienceart.com\/tr\/wp-json\/wp\/v2\/posts\/1575\/revisions\/1576"}],"wp:attachment":[{"href":"https:\/\/www.lifescienceart.com\/tr\/wp-json\/wp\/v2\/media?parent=1575"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.lifescienceart.com\/tr\/wp-json\/wp\/v2\/categories?post=1575"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.lifescienceart.com\/tr\/wp-json\/wp\/v2\/tags?post=1575"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}