[{"data":1,"prerenderedAt":136},["ShallowReactive",2],{"project-34748677":3},{"id":4,"name":5,"line":6,"line_source":7,"title":8,"url":9,"domain":10,"maker":11,"posted_at":12,"year":13,"points":14,"comments":15,"rank_in_year":16,"shown_in_year":17,"top":18,"tier":19,"category":20,"subcategory":21,"format":22,"keywords":23,"reception":29,"sentiment":30,"stance_mix":31,"scored_comments":33,"aspects":34,"strip":36,"post_text":38,"what":39,"said":61,"maker_in_thread":90,"shape":92,"grid":94,"attempts":99,"same_week":100,"maker_shows":37,"maker_hidden":129,"reader_version":130,"card":131},"34748677","Sauron","A live news visualization map","title","Show HN: Sauron – A live news visualization map","https:\u002F\u002Fsauron.matthew.science","sauron.matthew.science","sodality2",1676079814,2023,11,2,2329,3109,75,"shown","data","news visualization map","web_app",[24,25,26,27,28],"news map","breaking news","wikidata","nlp geolocation","live news visualization","quiet",null,{"positive":32,"neutral":33,"mixed":32,"critical":32},0,1,{"privacy":35},{"positive":32,"critical":32},[37,32],3,"Hello! I'd like to share a demo I made that parses breaking news and displays the location based on referenced entities within the tweet text. It utilizes NLP and WikiData to identify and fetch the data.",{"problem":40,"audience":30,"pricing":30,"motivation":46,"time_to_build":30,"stack":50,"openness":59,"stage":60,"team_size":59},{"value":41,"source":42,"evidence":43},"Showing where breaking news happens by mapping locations referenced in tweets","maker",[44],{"id":45},"post",{"value":47,"source":42,"evidence":48},"Demo of parsing breaking news and locating entities",[49],{"id":45},[51,55],{"value":52,"source":42,"evidence":53},"NLP",[54],{"id":45},{"value":56,"source":42,"evidence":57},"WikiData",[58],{"id":45},"unknown","prototype",{"praise":62,"objections":71,"requests":76,"questions":77,"alternatives":89},[63],{"value":64,"source":65,"evidence":66},"Interesting demo of the idea","commenter",[67],{"id":68,"by":69,"text":70},"34748706","philiproberts","Very cool! I wonder how this could be used to search for violations of personal privacy on Twitter.",[72],{"value":73,"source":65,"evidence":74},"Could enable searching for violations of personal privacy on Twitter",[75],{"id":68,"by":69,"text":70},[],[78,82],{"value":79,"source":65,"evidence":80},"Could it be used to find privacy violations on Twitter?",[81],{"id":68,"by":69,"text":70},{"value":83,"source":65,"evidence":84},"Could it detect sarcasm in veiled threats?",[85],{"id":86,"by":87,"text":88},"34748851","rman666","Or even how it might be used to find sarcasm in veiled threats!",[],{"comments":32,"answered":32,"key":91},[],{"commenters":15,"max_depth":15,"maker_replies":32,"first_comment_mins":93,"lifespan_hours":32},5,[95,97],[68,32,37,96,69,32],"project\u002Fneutral\u002Fprivacy",[86,32,32,98,87,32],"other\u002Fneutral\u002Fprivacy",[],[101,106,111,115,119,124],{"id":102,"name":103,"points":104,"category":105},"34729849","ScreenStab",497,"creative",{"id":107,"name":108,"points":109,"category":110},"34730520","boxxy",384,"dev_tools",{"id":112,"name":113,"points":114,"category":105},"34795155","Peel",353,{"id":116,"name":117,"points":118,"category":110},"34740529","Spaghettify",323,{"id":120,"name":121,"points":122,"category":123},"34780579","Paperlist",287,"learning_science",{"id":125,"name":126,"points":127,"category":128},"34770898","WAAS",267,"ai",false,"v2",{"id":132,"name":5,"line":6,"ai":129,"cat":20,"year":13,"points":14,"comments":15,"rec":29,"s":30,"top":18,"kw":133,"maker":11,"domain":10,"tier":19,"attempts":32,"strip":134,"url":9,"mix":135,"praise":64,"objection":73,"sub":21},34748677,[24,25,26,27,28],"30",[32,33,32,32],1794036631096]