Catholic Impact Evolution Through Public Twitter Data During COVID-19
During the Covid-19 crisis, many networks have sprung up disseminating information. This study examines the influence of religion during the Covid-19 pandemic. It understands religion as a factor capable of mitigating frustrations and critical situations in society. To this end, a data mining analys...
Gespeichert in:
| Veröffentlicht in: | International journal of cloud applications and computing 2022, Vol.12 (1), p.1-17 |
|---|---|
| Hauptverfasser: | , , , |
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | 17 |
|---|---|
| container_issue | 1 |
| container_start_page | 1 |
| container_title | International journal of cloud applications and computing |
| container_volume | 12 |
| creator | Marín, Enrique Caño González-Tejero, Cristina Blanco García, María Guijarro García, F Javier Sendra |
| description | During the Covid-19 crisis, many networks have sprung up disseminating information. This study examines the influence of religion during the Covid-19 pandemic. It understands religion as a factor capable of mitigating frustrations and critical situations in society. To this end, a data mining analysis was developed for a set of 107,786 tweets collected from the social platform Twitter in the framework of user-generated content (UGC), linked to the Covid-19 related tweets published by @Pontifex and @Pontifex_es. To achieve this goal, hidden insight data extraction and sentiment analysis are carried out, along with the application of Social Network Analysis (SNA) techniques. The main outcome of the study is the positive correlation between the repercussion of the Pope’s tweets and the evolution of the Covid-19 incidence in Europe. Finally, the Latent Dirichlet Allocation (LDA) algorithm identifies the relevant topics in the analysis. |
| doi_str_mv | 10.4018/IJCAC.305211 |
| format | Article |
| fullrecord | <record><control><sourceid>gale_proqu</sourceid><recordid>TN_cdi_proquest_journals_2807883585</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><galeid>A759922883</galeid><sourcerecordid>A759922883</sourcerecordid><originalsourceid>FETCH-LOGICAL-c303t-768d7ac11dfdd8bfa8e58f975f5f33661d2bb585247c987acd97c5df790f4afc3</originalsourceid><addsrcrecordid>eNptkctOwzAQRSMEElXpjg-IxJYUP-LEWVZpgaBKZVHYWo4TJ67auNgOiL_HJahlUS_GI82Zh-4NglsIpjGA9KF4yWf5FAOCILwIRgiSJIIUJZfHHMfXwcTaDfCPxBTgeBQscu5avVUiLHZ7Lly4-NTb3indhevW6L5pw9e-PNTXX8q52oRz7ng4743qmjBfvRfzCGY3wZXkW1tP_v5x8Pa4WOfP0XL1VOSzZSQwwC5KE1qlXEBYyaqipeS0JlRmKZFEYpwksEJlSShBcSoy6skqSwWpZJoBGXMp8Di4G-bujf7oa-vYRvem8ysZoiClFPvuE9Xwbc1UJ7UzXOyUFWyWkixDyIOeuv9Hlb1VXW19sKppnW14b-1ZXBhtrakl2xu14-abQcAOBrBfA9hggMfzAVeNOh15EJoNQrOj0MwLfW4GRPgHjeWMHg</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2807883585</pqid></control><display><type>article</type><title>Catholic Impact Evolution Through Public Twitter Data During COVID-19</title><source>ProQuest Central</source><creator>Marín, Enrique Caño ; González-Tejero, Cristina Blanco ; García, María Guijarro ; García, F Javier Sendra</creator><creatorcontrib>Marín, Enrique Caño ; González-Tejero, Cristina Blanco ; García, María Guijarro ; García, F Javier Sendra</creatorcontrib><description>During the Covid-19 crisis, many networks have sprung up disseminating information. This study examines the influence of religion during the Covid-19 pandemic. It understands religion as a factor capable of mitigating frustrations and critical situations in society. To this end, a data mining analysis was developed for a set of 107,786 tweets collected from the social platform Twitter in the framework of user-generated content (UGC), linked to the Covid-19 related tweets published by @Pontifex and @Pontifex_es. To achieve this goal, hidden insight data extraction and sentiment analysis are carried out, along with the application of Social Network Analysis (SNA) techniques. The main outcome of the study is the positive correlation between the repercussion of the Pope’s tweets and the evolution of the Covid-19 incidence in Europe. Finally, the Latent Dirichlet Allocation (LDA) algorithm identifies the relevant topics in the analysis.</description><identifier>ISSN: 2156-1834</identifier><identifier>EISSN: 2156-1826</identifier><identifier>DOI: 10.4018/IJCAC.305211</identifier><language>eng</language><publisher>Hershey: IGI Global</publisher><subject>Algorithms ; Analysis ; Data analysis ; Data mining ; Dirichlet problem ; Epidemics ; Evolution ; Network analysis ; Religion ; Sentiment analysis ; Social networks ; Spain ; United Kingdom ; User generated content</subject><ispartof>International journal of cloud applications and computing, 2022, Vol.12 (1), p.1-17</ispartof><rights>COPYRIGHT 2022 IGI Global</rights><rights>Copyright © 2022, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c303t-768d7ac11dfdd8bfa8e58f975f5f33661d2bb585247c987acd97c5df790f4afc3</citedby><cites>FETCH-LOGICAL-c303t-768d7ac11dfdd8bfa8e58f975f5f33661d2bb585247c987acd97c5df790f4afc3</cites><orcidid>0000-0002-7948-1657 ; 0000-0002-4039-2278</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.proquest.com/docview/2807883585?pq-origsite=primo$$EHTML$$P50$$Gproquest$$H</linktohtml><link.rule.ids>314,780,784,4024,21388,27923,27924,27925,33744,43805,64385,64389,72469</link.rule.ids></links><search><creatorcontrib>Marín, Enrique Caño</creatorcontrib><creatorcontrib>González-Tejero, Cristina Blanco</creatorcontrib><creatorcontrib>García, María Guijarro</creatorcontrib><creatorcontrib>García, F Javier Sendra</creatorcontrib><title>Catholic Impact Evolution Through Public Twitter Data During COVID-19</title><title>International journal of cloud applications and computing</title><description>During the Covid-19 crisis, many networks have sprung up disseminating information. This study examines the influence of religion during the Covid-19 pandemic. It understands religion as a factor capable of mitigating frustrations and critical situations in society. To this end, a data mining analysis was developed for a set of 107,786 tweets collected from the social platform Twitter in the framework of user-generated content (UGC), linked to the Covid-19 related tweets published by @Pontifex and @Pontifex_es. To achieve this goal, hidden insight data extraction and sentiment analysis are carried out, along with the application of Social Network Analysis (SNA) techniques. The main outcome of the study is the positive correlation between the repercussion of the Pope’s tweets and the evolution of the Covid-19 incidence in Europe. Finally, the Latent Dirichlet Allocation (LDA) algorithm identifies the relevant topics in the analysis.</description><subject>Algorithms</subject><subject>Analysis</subject><subject>Data analysis</subject><subject>Data mining</subject><subject>Dirichlet problem</subject><subject>Epidemics</subject><subject>Evolution</subject><subject>Network analysis</subject><subject>Religion</subject><subject>Sentiment analysis</subject><subject>Social networks</subject><subject>Spain</subject><subject>United Kingdom</subject><subject>User generated content</subject><issn>2156-1834</issn><issn>2156-1826</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>N95</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNptkctOwzAQRSMEElXpjg-IxJYUP-LEWVZpgaBKZVHYWo4TJ67auNgOiL_HJahlUS_GI82Zh-4NglsIpjGA9KF4yWf5FAOCILwIRgiSJIIUJZfHHMfXwcTaDfCPxBTgeBQscu5avVUiLHZ7Lly4-NTb3indhevW6L5pw9e-PNTXX8q52oRz7ng4743qmjBfvRfzCGY3wZXkW1tP_v5x8Pa4WOfP0XL1VOSzZSQwwC5KE1qlXEBYyaqipeS0JlRmKZFEYpwksEJlSShBcSoy6skqSwWpZJoBGXMp8Di4G-bujf7oa-vYRvem8ysZoiClFPvuE9Xwbc1UJ7UzXOyUFWyWkixDyIOeuv9Hlb1VXW19sKppnW14b-1ZXBhtrakl2xu14-abQcAOBrBfA9hggMfzAVeNOh15EJoNQrOj0MwLfW4GRPgHjeWMHg</recordid><startdate>2022</startdate><enddate>2022</enddate><creator>Marín, Enrique Caño</creator><creator>González-Tejero, Cristina Blanco</creator><creator>García, María Guijarro</creator><creator>García, F Javier Sendra</creator><general>IGI Global</general><scope>AAYXX</scope><scope>CITATION</scope><scope>N95</scope><scope>8FE</scope><scope>8FG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>JQ2</scope><scope>K7-</scope><scope>P5Z</scope><scope>P62</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><orcidid>https://orcid.org/0000-0002-7948-1657</orcidid><orcidid>https://orcid.org/0000-0002-4039-2278</orcidid></search><sort><creationdate>2022</creationdate><title>Catholic Impact Evolution Through Public Twitter Data During COVID-19</title><author>Marín, Enrique Caño ; González-Tejero, Cristina Blanco ; García, María Guijarro ; García, F Javier Sendra</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c303t-768d7ac11dfdd8bfa8e58f975f5f33661d2bb585247c987acd97c5df790f4afc3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Algorithms</topic><topic>Analysis</topic><topic>Data analysis</topic><topic>Data mining</topic><topic>Dirichlet problem</topic><topic>Epidemics</topic><topic>Evolution</topic><topic>Network analysis</topic><topic>Religion</topic><topic>Sentiment analysis</topic><topic>Social networks</topic><topic>Spain</topic><topic>United Kingdom</topic><topic>User generated content</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Marín, Enrique Caño</creatorcontrib><creatorcontrib>González-Tejero, Cristina Blanco</creatorcontrib><creatorcontrib>García, María Guijarro</creatorcontrib><creatorcontrib>García, F Javier Sendra</creatorcontrib><collection>CrossRef</collection><collection>Gale Business: Insights</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Central</collection><collection>Advanced Technologies & Aerospace Collection</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Computer Science Collection</collection><collection>Computer Science Database</collection><collection>ProQuest advanced technologies & aerospace journals</collection><collection>ProQuest Advanced Technologies & Aerospace Collection</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><jtitle>International journal of cloud applications and computing</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Marín, Enrique Caño</au><au>González-Tejero, Cristina Blanco</au><au>García, María Guijarro</au><au>García, F Javier Sendra</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Catholic Impact Evolution Through Public Twitter Data During COVID-19</atitle><jtitle>International journal of cloud applications and computing</jtitle><date>2022</date><risdate>2022</risdate><volume>12</volume><issue>1</issue><spage>1</spage><epage>17</epage><pages>1-17</pages><issn>2156-1834</issn><eissn>2156-1826</eissn><abstract>During the Covid-19 crisis, many networks have sprung up disseminating information. This study examines the influence of religion during the Covid-19 pandemic. It understands religion as a factor capable of mitigating frustrations and critical situations in society. To this end, a data mining analysis was developed for a set of 107,786 tweets collected from the social platform Twitter in the framework of user-generated content (UGC), linked to the Covid-19 related tweets published by @Pontifex and @Pontifex_es. To achieve this goal, hidden insight data extraction and sentiment analysis are carried out, along with the application of Social Network Analysis (SNA) techniques. The main outcome of the study is the positive correlation between the repercussion of the Pope’s tweets and the evolution of the Covid-19 incidence in Europe. Finally, the Latent Dirichlet Allocation (LDA) algorithm identifies the relevant topics in the analysis.</abstract><cop>Hershey</cop><pub>IGI Global</pub><doi>10.4018/IJCAC.305211</doi><tpages>17</tpages><orcidid>https://orcid.org/0000-0002-7948-1657</orcidid><orcidid>https://orcid.org/0000-0002-4039-2278</orcidid></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 2156-1834 |
| ispartof | International journal of cloud applications and computing, 2022, Vol.12 (1), p.1-17 |
| issn | 2156-1834 2156-1826 |
| language | eng |
| recordid | cdi_proquest_journals_2807883585 |
| source | ProQuest Central |
| subjects | Algorithms Analysis Data analysis Data mining Dirichlet problem Epidemics Evolution Network analysis Religion Sentiment analysis Social networks Spain United Kingdom User generated content |
| title | Catholic Impact Evolution Through Public Twitter Data During COVID-19 |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-20T17%3A45%3A15IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-gale_proqu&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Catholic%20Impact%20Evolution%20Through%20Public%20Twitter%20Data%20During%20COVID-19&rft.jtitle=International%20journal%20of%20cloud%20applications%20and%20computing&rft.au=Mar%C3%ADn,%20Enrique%20Ca%C3%B1o&rft.date=2022&rft.volume=12&rft.issue=1&rft.spage=1&rft.epage=17&rft.pages=1-17&rft.issn=2156-1834&rft.eissn=2156-1826&rft_id=info:doi/10.4018/IJCAC.305211&rft_dat=%3Cgale_proqu%3EA759922883%3C/gale_proqu%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2807883585&rft_id=info:pmid/&rft_galeid=A759922883&rfr_iscdi=true |