{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,13]],"date-time":"2026-02-13T09:17:42Z","timestamp":1770974262883,"version":"3.50.1"},"reference-count":31,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2015,3,5]],"date-time":"2015-03-05T00:00:00Z","timestamp":1425513600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"NSF IGERT Big Data-Social Science","award":["DGE-1144860"],"award-info":[{"award-number":["DGE-1144860"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJGI"],"abstract":"<jats:p>We introduce spatial patterns of Tweets visualization (SPoTvis), a web-based geovisual analytics tool for exploring messages on Twitter (or \u201ctweets\u201d) collected about political discourse, and illustrate the potential of the approach with a case study focused on a set of linked political events in the United States. In October 2013, the U.S. Congressional debate over the allocation of funds to the Patient Protection and Affordable Care Act (commonly known as the ACA or \u201cObamacare\u201d) culminated in a 16-day government shutdown. Meanwhile the online health insurance marketplace related to the ACA was making a public debut hampered by performance and functionality problems. Messages on Twitter during this time period included sharply divided opinions about these events, with many people angry about the shutdown and others supporting the delay of the ACA implementation. SPoTvis supports the analysis of these events using an interactive map connected dynamically to a term polarity plot; through the SPoTvis interface, users can compare the dominant subthemes of Tweets in any two states or congressional districts. Demographic attributes and political information on the display, coupled with functionality to show (dis)similar features, enrich users\u2019 understandings of the units being compared. Relationships among places, politics and discourse on Twitter are quantified using statistical analyses and explored visually using SPoTvis. A two-part user study evaluates SPoTvis\u2019 ability to enable insight discovery, as well as the tool\u2019s design, functionality and applicability to other contexts.<\/jats:p>","DOI":"10.3390\/ijgi4010337","type":"journal-article","created":{"date-parts":[[2015,3,5]],"date-time":"2015-03-05T10:43:07Z","timestamp":1425552187000},"page":"337-366","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":18,"title":["Geovisual Analytics Approach to Exploring Public Political Discourse on Twitter"],"prefix":"10.3390","volume":"4","author":[{"given":"Jonathan","family":"Nelson","sequence":"first","affiliation":[{"name":"GeoVISTA Center, Department of Geography, Penn State University, State College, PA 16801, USA"}]},{"given":"Sterling","family":"Quinn","sequence":"additional","affiliation":[{"name":"GeoVISTA Center, Department of Geography, Penn State University, State College, PA 16801, USA"}]},{"given":"Brian","family":"Swedberg","sequence":"additional","affiliation":[{"name":"GeoVISTA Center, Department of Geography, Penn State University, State College, PA 16801, USA"}]},{"given":"Wanghuan","family":"Chu","sequence":"additional","affiliation":[{"name":"Department of Statistics, Penn State University, State College, PA 16801, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0356-7323","authenticated-orcid":false,"given":"Alan","family":"MacEachren","sequence":"additional","affiliation":[{"name":"GeoVISTA Center, Department of Geography, Penn State University, State College, PA 16801, USA"}]}],"member":"1968","published-online":{"date-parts":[[2015,3,5]]},"reference":[{"key":"ref_1","unstructured":"Thomas, J.J., and Cook, K.A. 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