<?xml version="1.0" encoding="UTF-8"?><rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:dcq="http://purl.org/dc/terms/"><records count="1" morepages="false" start="1" end="1"><record rownumber="1"><dc:product_type>Journal Article</dc:product_type><dc:title>Geographic context-aware text mining: enhance social media message classification for situational awareness by integrating spatial and temporal features</dc:title><dc:creator>Scheele, Christopher; Yu, Manzhu; Huang, Qunying</dc:creator><dc:corporate_author/><dc:editor/><dc:description/><dc:publisher/><dc:date>2021-11-02</dc:date><dc:nsf_par_id>10313627</dc:nsf_par_id><dc:journal_name>International Journal of Digital Earth</dc:journal_name><dc:journal_volume>14</dc:journal_volume><dc:journal_issue>11</dc:journal_issue><dc:page_range_or_elocation/><dc:issn>1753-8947</dc:issn><dc:isbn/><dc:doi>https://doi.org/10.1080/17538947.2021.1968048</dc:doi><dcq:identifierAwardId>1940091</dcq:identifierAwardId><dc:subject/><dc:version_number/><dc:location/><dc:rights/><dc:institution/><dc:sponsoring_org>National Science Foundation</dc:sponsoring_org></record></records></rdf:RDF>