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Measuring and mapping long-term changes in migration flows using population-scale family tree data / Caglar Koylu in Cartography and Geographic Information Science, vol 49 n° 2 (February 2022)  

Public [article]  inCartography and Geographic Information Science > vol 49 n° 2 (February 2022) . - pp 154 - 170 Titre : Measuring and mapping long-term changes in migration flows using population-scale family tree data Type de document : Article/Communication Auteurs : Caglar Koylu, Auteur ; Alice Kasakoff, Auteur Année de publication : 2022 Article en page(s) : pp 154 - 170 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Cartographie thématique [Termes IGN] analyse diachronique [Termes IGN] cartographie des flux [Termes IGN] données localisées des bénévoles [Termes IGN] Etats-Unis [Termes IGN] généalogie [Termes IGN] histoire [Termes IGN] migration humaine [Termes IGN] origine - destination [Termes IGN] représentation du changement Résumé : (auteur) Studying migration over a long period is challenging due to lack of data, uneven data quality, and the methodological challenges that arise when analyzing migration over large geographic areas and long time spans with constantly changing political boundaries. Crowd-sourced family tree data are an untapped source of volunteered geographic information generated by millions of users. These trees contain information on individuals such as birth and death places and years, and kinship ties, and have the potential to support analysis of population dynamics and migration over many generations and far into the past. In this article, we introduce a methodology to measure and map long-term changes in migration flows using a population-scale family-tree data set. Our methodology includes many steps such as extracting migration events, temporal periodization, gravity normalization, and producing time-series flow maps. We study internal migration in the continental United States between 1789 and 1924 using birthplaces and birthyears of children from a cleaned, geocoded, and connected set of family trees from Rootsweb.com. To the best of our knowledge, the results are the first migration flow maps that show how the internal migration flows within the U.S. changed over such a long period of time (i.e. 135 years). Numéro de notice : A2022-138 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/15230406.2021.2011419 Date de publication en ligne : 19/01/2022 En ligne : https://doi.org/10.1080/15230406.2021.2011419 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99759 [article]

Connecting family trees to construct a population-scale and longitudinal geo-social network for the U.S. / Caglar Koylu in International journal of geographical information science IJGIS, vol 35 n° 12 (December 2021)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 35 n° 12 (December 2021) . - pp 2380 - 2423 Titre : Connecting family trees to construct a population-scale and longitudinal geo-social network for the U.S. Type de document : Article/Communication Auteurs : Caglar Koylu, Auteur ; Diansheng Guo, Auteur ; Yuan Huang, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 2380 - 2423 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web [Termes IGN] appariement sémantique [Termes IGN] collecte de données [Termes IGN] démographie [Termes IGN] dix-neuvième siècle [Termes IGN] données localisées des bénévoles [Termes IGN] données publiques [Termes IGN] Etats-Unis [Termes IGN] généalogie [Termes IGN] géocodage [Termes IGN] historique des données [Termes IGN] itération [Termes IGN] migration humaine [Termes IGN] mobilité [Termes IGN] réseau social géodépendant [Termes IGN] système d'information historique Résumé : (auteur) We collected 92,832 user-contributed and publicly available family trees from rootsweb.com, including 250 million individuals who were born in North America and Europe between 1630 and 1930. We cleaned and connected the family trees to create a population-scale and longitudinal family tree dataset using a workflow of data collection and cleaning, geocoding, fuzzy record linkage and a relation-based iterative search for connecting trees and deduplication of records. Given the largest connected component of nearly 40 million individuals, and a total of 80 million individuals, we generated, to date, the largest population-scale and longitudinal geo-social network over centuries. We evaluated the representativeness of the family tree dataset for historical population demography and mobility by comparing the data to the 1880 Census. Our results showed that the family trees were biased towards males, the elderly, farmers, and native-born white segments of the population. Individuals were highly mobile – in our 1880 sample of parent-child pairs where both were born in the U.S., 47% were born in different states. Our findings agreed with prior studies that people migrated from East to West in horizontal bands, and the trend was reflected in the dialects and regional structure of the U.S. Numéro de notice : A2021-876 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2020.1821885 Date de publication en ligne : 30/09/2020 En ligne : https://doi.org/10.1080/13658816.2020.1821885 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99139 [article]

Modeling and visualizing semantic and spatio-temporal evolution of topics in interpersonal communication on Twitter / Caglar Koylu in International journal of geographical information science IJGIS, Vol 33 n° 3-4 (March - April 2019)  

Public [article]  inInternational journal of geographical information science IJGIS > Vol 33 n° 3-4 (March - April 2019) . - pp 805 - 832 Titre : Modeling and visualizing semantic and spatio-temporal evolution of topics in interpersonal communication on Twitter Type de document : Article/Communication Auteurs : Caglar Koylu, Auteur Année de publication : 2019 Article en page(s) : pp 805 - 832 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web [Termes IGN] analyse diachronique [Termes IGN] analyse géovisuelle [Termes IGN] analyse spatio-temporelle [Termes IGN] comportement [Termes IGN] réseau social [Termes IGN] segmentation sémantique [Termes IGN] traitement interactif [Termes IGN] Twitter Résumé : (Auteur) Interpersonal communication on online social networks has a significant impact on the society by not only diffusing information, but also forming social ties, norms, and behaviors. Knowing how the conversational discourse semantically and geographically vary over time can help uncover the changing dynamics of interpersonal ties and the digital traces of social events. This article introduces a framework for modeling and visualizing the semantic and spatio-temporal evolution of topics in a spatially embedded and time-stamped interpersonal communication network. The framework consists of (1) a topic modeling workflow for modeling topics and extracting the evolution of conversational discourse; (2) a geo-social network modeling and smoothing approach to projecting connection characteristics and semantics of communication onto geographic space and time; (3) a web-based geovisual analytics environment for exploring semantic and spatio-temporal evolution of topics in a spatially embedded and time-stamped interpersonal communication network. To demonstrate, geo-located and reciprocal user mention and reply tweets over the course of the 2016 primary and presidential elections in the United States from 1 August 2015 to 15 November 2016 were analyzed. The large portion of the topics extracted from mention tweets were related to daily life routines, human activities, and interests such as school, work, sports, dating, wearing, birthday celebration, music, food, and live-tweeting. Specific focus on the analysis of political conversations revealed that the content of conversational discourse was split between civil rights and election-related discussions of the political campaigns and candidates. These political topics exhibited major shifts in terms of content and the popularity in reaction to primaries, debates, and events throughout the study period. While civil rights discussions were more dominant and in higher intensity across the nation and throughout the whole time period, election-specific conversations resulted in temporally varying local hotspots that correlated with locations of primaries and events. Numéro de notice : A2019-217 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2018.1458987 Date de publication en ligne : 25/04/2018 En ligne : https://doi.org/10.1080/13658816.2018.1458987 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92689 [article]

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CarSenToGram: geovisual text analytics for exploring spatiotemporal variation in public discourse on Twitter / Caglar Koylu in Cartography and Geographic Information Science, Vol 46 n° 1 (January 2019)  

Public [article]  inCartography and Geographic Information Science > Vol 46 n° 1 (January 2019) . - pp 57 - 71 Titre : CarSenToGram: geovisual text analytics for exploring spatiotemporal variation in public discourse on Twitter Type de document : Article/Communication Auteurs : Caglar Koylu, Auteur ; Ryan Larson, Auteur ; Bryce J. Dietrich, Auteur ; Kang-Pyo Lee, Auteur Année de publication : 2019 Article en page(s) : pp 57 - 71 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] analyse du discours [Termes IGN] analyse géovisuelle [Termes IGN] cartogramme [Termes IGN] contenu généré par les utilisateurs [Termes IGN] corpus [Termes IGN] données issues des réseaux sociaux [Termes IGN] exploration de données [Termes IGN] sentiment [Termes IGN] Twitter [Vedettes matières IGN] Géovisualisation Résumé : (auteur) Assessing the impact of events on the evolution of online public discourse is challenging due to the lack of data prior to the event and appropriate methodologies for capturing the progression of tenor of public discourse, both in terms of their tone and topic. In this article, we introduce a geovisual analytics framework, CarSenToGram, which integrates topic modeling and sentiment analysis with cartograms to identify the changing dynamics of public discourse on a particular topic across space and time. The main novelty of CarSenToGram is coupling comprehensible spatiotemporal overviews of the overall distribution, topical and sentiment patterns with increasing levels of information supported by zoom and filter, and details-on-demand interactions. To demonstrate the utility of CarSenToGram, in this article, we analyze tweets related to immigration the month before and after the 27 January 2017 travel ban in order to reveal insights into one of the defining moments of President Trump’s first year in office. Not only do we find that the travel ban influenced online public discourse and sentiment on immigration, but it also highlighted important partisan divisions within the US. Numéro de notice : A2019-012 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/15230406.2018.1510343 Date de publication en ligne : 18/09/2018 En ligne : https://doi.org/10.1080/15230406.2018.1510343 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91661 [article]

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