Do Global Cities Enable Global Views? Using Twitter to Quantify the Level of Geographical Awareness of U.S. Cities
Dynamic social media content, such as Twitter messages, can be used to examine individuals' beliefs and perceptions. By analyzing Twitter messages, this study examines how Twitter users exchanged and recognized toponyms (city names) for different cities in the United States. The frequency and v...
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| description | Dynamic social media content, such as Twitter messages, can be used to examine individuals' beliefs and perceptions. By analyzing Twitter messages, this study examines how Twitter users exchanged and recognized toponyms (city names) for different cities in the United States. The frequency and variety of city names found in their online conversations were used to identify the unique spatiotemporal patterns of "geographical awareness" for Twitter users. A new analytic method, Knowledge Discovery in Cyberspace for Geographical Awareness (KDCGA), is introduced to help identify the dynamic spatiotemporal patterns of geographic awareness among social media conversations. Twitter data were collected across 50 U.S. cities. Thousands of city names around the world were extracted from a large volume of Twitter messages (over 5 million tweets) by using the Twitter Application Programming Interface (APIs) and Python language computer programs. The percentages of distant city names (cities located in distant states or other countries far away from the locations of Twitter users) were used to estimate the level of global geographical awareness for Twitter users in each U.S. city. A Global awareness index (GAI) was developed to quantify the level of geographical awareness of Twitter users from within the same city. Our findings are that: (1) the level of geographical awareness varies depending on when and where Twitter messages are posted, yet Twitter users from big cities are more aware of the names of international cities or distant US cities than users from mid-size cities; (2) Twitter users have an increased awareness of other city names far away from their home city during holiday seasons; and (3) Twitter users are more aware of nearby city names than distant city names, and more aware of big city names rather than small city names. |
| doi_str_mv | 10.1371/journal.pone.0132464 |
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Using Twitter to Quantify the Level of Geographical Awareness of U.S. Cities</title><source>MEDLINE</source><source>DOAJ Directory of Open Access Journals</source><source>Public Library of Science</source><source>PubMed Central</source><source>Free Full-Text Journals in Chemistry</source><source>EZB Electronic Journals Library</source><creator>Han, Su Yeon ; Tsou, Ming-Hsiang ; Clarke, Keith C</creator><contributor>Hernandez Montoya, Alejandro Raul</contributor><creatorcontrib>Han, Su Yeon ; Tsou, Ming-Hsiang ; Clarke, Keith C ; Hernandez Montoya, Alejandro Raul</creatorcontrib><description>Dynamic social media content, such as Twitter messages, can be used to examine individuals' beliefs and perceptions. By analyzing Twitter messages, this study examines how Twitter users exchanged and recognized toponyms (city names) for different cities in the United States. The frequency and variety of city names found in their online conversations were used to identify the unique spatiotemporal patterns of "geographical awareness" for Twitter users. A new analytic method, Knowledge Discovery in Cyberspace for Geographical Awareness (KDCGA), is introduced to help identify the dynamic spatiotemporal patterns of geographic awareness among social media conversations. Twitter data were collected across 50 U.S. cities. Thousands of city names around the world were extracted from a large volume of Twitter messages (over 5 million tweets) by using the Twitter Application Programming Interface (APIs) and Python language computer programs. The percentages of distant city names (cities located in distant states or other countries far away from the locations of Twitter users) were used to estimate the level of global geographical awareness for Twitter users in each U.S. city. A Global awareness index (GAI) was developed to quantify the level of geographical awareness of Twitter users from within the same city. Our findings are that: (1) the level of geographical awareness varies depending on when and where Twitter messages are posted, yet Twitter users from big cities are more aware of the names of international cities or distant US cities than users from mid-size cities; (2) Twitter users have an increased awareness of other city names far away from their home city during holiday seasons; and (3) Twitter users are more aware of nearby city names than distant city names, and more aware of big city names rather than small city names.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0132464</identifier><identifier>PMID: 26167942</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Awareness ; Big Data ; Cartography ; Cities ; Cities - statistics & numerical data ; Communication ; Computer programs ; Data mining ; Data processing ; Digital media ; Geodemographics ; Geographic information science ; Geography ; Global positioning systems ; Globalization ; GPS ; Human geography ; Humans ; International conferences ; Internationality ; Internet ; Messages ; Models, Statistical ; Names ; Programming languages ; Securities markets ; Social Media - statistics & numerical data ; Social networks ; Social research ; Software ; Stock exchanges ; Studies ; United States</subject><ispartof>PloS one, 2015-07, Vol.10 (7), p.e0132464-e0132464</ispartof><rights>COPYRIGHT 2015 Public Library of Science</rights><rights>2015 Han et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2015 Han et al 2015 Han et al</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c692t-6aa9c717d1bc37d91aff9d304a0aaaf22a8c0ac895828a19c9e078b2800f70b23</citedby><cites>FETCH-LOGICAL-c692t-6aa9c717d1bc37d91aff9d304a0aaaf22a8c0ac895828a19c9e078b2800f70b23</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC4500559/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC4500559/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,723,776,780,860,881,2095,2914,23846,27903,27904,53769,53771,79346,79347</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/26167942$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><contributor>Hernandez Montoya, Alejandro Raul</contributor><creatorcontrib>Han, Su Yeon</creatorcontrib><creatorcontrib>Tsou, Ming-Hsiang</creatorcontrib><creatorcontrib>Clarke, Keith C</creatorcontrib><title>Do Global Cities Enable Global Views? Using Twitter to Quantify the Level of Geographical Awareness of U.S. Cities</title><title>PloS one</title><addtitle>PLoS One</addtitle><description>Dynamic social media content, such as Twitter messages, can be used to examine individuals' beliefs and perceptions. By analyzing Twitter messages, this study examines how Twitter users exchanged and recognized toponyms (city names) for different cities in the United States. The frequency and variety of city names found in their online conversations were used to identify the unique spatiotemporal patterns of "geographical awareness" for Twitter users. A new analytic method, Knowledge Discovery in Cyberspace for Geographical Awareness (KDCGA), is introduced to help identify the dynamic spatiotemporal patterns of geographic awareness among social media conversations. Twitter data were collected across 50 U.S. cities. Thousands of city names around the world were extracted from a large volume of Twitter messages (over 5 million tweets) by using the Twitter Application Programming Interface (APIs) and Python language computer programs. The percentages of distant city names (cities located in distant states or other countries far away from the locations of Twitter users) were used to estimate the level of global geographical awareness for Twitter users in each U.S. city. A Global awareness index (GAI) was developed to quantify the level of geographical awareness of Twitter users from within the same city. 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Academic</collection><collection>PubMed Central (Full Participant titles)</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>PloS one</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Han, Su Yeon</au><au>Tsou, Ming-Hsiang</au><au>Clarke, Keith C</au><au>Hernandez Montoya, Alejandro Raul</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Do Global Cities Enable Global Views? Using Twitter to Quantify the Level of Geographical Awareness of U.S. Cities</atitle><jtitle>PloS one</jtitle><addtitle>PLoS One</addtitle><date>2015-07-13</date><risdate>2015</risdate><volume>10</volume><issue>7</issue><spage>e0132464</spage><epage>e0132464</epage><pages>e0132464-e0132464</pages><issn>1932-6203</issn><eissn>1932-6203</eissn><abstract>Dynamic social media content, such as Twitter messages, can be used to examine individuals' beliefs and perceptions. By analyzing Twitter messages, this study examines how Twitter users exchanged and recognized toponyms (city names) for different cities in the United States. The frequency and variety of city names found in their online conversations were used to identify the unique spatiotemporal patterns of "geographical awareness" for Twitter users. A new analytic method, Knowledge Discovery in Cyberspace for Geographical Awareness (KDCGA), is introduced to help identify the dynamic spatiotemporal patterns of geographic awareness among social media conversations. Twitter data were collected across 50 U.S. cities. Thousands of city names around the world were extracted from a large volume of Twitter messages (over 5 million tweets) by using the Twitter Application Programming Interface (APIs) and Python language computer programs. The percentages of distant city names (cities located in distant states or other countries far away from the locations of Twitter users) were used to estimate the level of global geographical awareness for Twitter users in each U.S. city. A Global awareness index (GAI) was developed to quantify the level of geographical awareness of Twitter users from within the same city. Our findings are that: (1) the level of geographical awareness varies depending on when and where Twitter messages are posted, yet Twitter users from big cities are more aware of the names of international cities or distant US cities than users from mid-size cities; (2) Twitter users have an increased awareness of other city names far away from their home city during holiday seasons; and (3) Twitter users are more aware of nearby city names than distant city names, and more aware of big city names rather than small city names.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>26167942</pmid><doi>10.1371/journal.pone.0132464</doi><oa>free_for_read</oa></addata></record> |
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| subjects | Awareness Big Data Cartography Cities Cities - statistics & numerical data Communication Computer programs Data mining Data processing Digital media Geodemographics Geographic information science Geography Global positioning systems Globalization GPS Human geography Humans International conferences Internationality Internet Messages Models, Statistical Names Programming languages Securities markets Social Media - statistics & numerical data Social networks Social research Software Stock exchanges Studies United States |
| title | Do Global Cities Enable Global Views? Using Twitter to Quantify the Level of Geographical Awareness of U.S. Cities |
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