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dc.date.available
2023-05-12T19:22:29Z  
dc.identifier.citation
Tommasel, Antonela; (2023): SpanishTweetsCOVID-19: A Social Media Enriched Covid-19 Twitter Spanish Dataset. Consejo Nacional de Investigaciones Científicas y Técnicas. (dataset). http://hdl.handle.net/11336/197411  
dc.identifier.uri
http://hdl.handle.net/11336/197411  
dc.description.abstract
This dataset presents a large-scale collection of millions of Twitter posts related to the coronavirus pandemic in Spanish language. The collection was built by monitoring public posts written in Spanish containing a diverse set of hashtags related to the COVID-19, as well as tweets shared by the official Argentinian government offices, such as ministries and secretaries at different levels. Data was collected between March and August 2020 using the Twitter API. In addition to tweets IDs, the dataset includes information about mentions, retweets, media, URLs, hashtags, replies, users and content-based user relations, allowing the observation of the dynamics of the shared information. Data is presented in different tables that can be analysed separately or combined. The dataset aims at serving as source for studying several coronavirus effects in people through social media, including the impact of public policies, the perception of risk and related disease consequences, the adoption of guidelines, the emergence, dynamics and propagation of disinformation and rumours, the formation of communities and other social phenomena, the evolution of health related indicators (such as fear, stress, sleep disorders, or children behaviour changes), among other possibilities. In this sense, the dataset can be useful for multi-disciplinary researchers related to the different fields of data science, social network analysis, social computing, medical informatics, social sciences, among others.  
dc.rights
info:eu-repo/semantics/openAccess  
dc.rights.uri
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/  
dc.title
SpanishTweetsCOVID-19: A Social Media Enriched Covid-19 Twitter Spanish Dataset  
dc.type
dataset  
dc.date.updated
2022-06-06T17:59:00Z  
dc.description.fil
Fil: Tommasel, Antonela. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Instituto Superior de Ingeniería del Software. Universidad Nacional del Centro de la Provincia de Buenos Aires. Instituto Superior de Ingeniería del Software; Argentina  
dc.datacite.PublicationYear
2023  
dc.datacite.Creator
Tommasel, Antonela  
dc.datacite.affiliation
Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Instituto Superior de Ingeniería del Software. Universidad Nacional del Centro de la Provincia de Buenos Aires. Instituto Superior de Ingeniería del Software  
dc.datacite.affiliation
Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Instituto Superior de Ingeniería del Software. Universidad Nacional del Centro de la Provincia de Buenos Aires. Instituto Superior de Ingeniería del Software  
dc.datacite.publisher
Consejo Nacional de Investigaciones Científicas y Técnicas  
dc.datacite.subject
Otras Ciencias de la Computación e Información  
dc.datacite.subject
Ciencias de la Computación e Información  
dc.datacite.subject
CIENCIAS NATURALES Y EXACTAS  
dc.datacite.ContributorType
RelatedPerson  
dc.datacite.ContributorName
Rodriguez, Juan Manuel  
dc.datacite.date
01/03/2020-31/10/2020  
dc.datacite.DateType
Recolectado  
dc.datacite.language
spa  
dc.datacite.AlternateIdentifierType
info:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.17632/nv8k69y59d.2  
dc.datacite.version
1.0  
dc.datacite.description
The raw data belonging to the Twitter posts were retrieved from the Twitter API using our own toll called Faking it!, which internally uses Twitter4J for easily integrating with the Twitter API. Faking it! can also be used to rehydrate the data collection. In all cases, longs are encoded as Radix 32 Strings. The code for processing and analysing the raw data and the shared tables is also available at the Faking it! repository at https://github.com/knife982000/FakingIt.  
dc.datacite.DescriptionType
Información Técnica  
dc.relationtype.isSourceOf
http://dx.doi.org/10.1108/IDD-01-2021-0003  
dc.relationtype.isSourceOf
https://ri.conicet.gov.ar/handle/11336/151779  
dc.subject.keyword
SOCIAL SCIENCES  
dc.subject.keyword
SOCIAL MEDIA  
dc.subject.keyword
MEDICAL INFORMATICS  
dc.subject.keyword
SOCIAL NETWORKS ANALYSIS  
dc.subject.keyword
SPANISH LANGUAGE  
dc.subject.keyword
TWITTER  
dc.subject.keyword
COVID-19  
dc.datacite.resourceTypeGeneral
dataset  
dc.conicet.datoinvestigacionid
742  
dc.conicet.justificacion
Si bien al momento de recolectar los tweets se incluyeron criterios geográficos, no todos los tweets incluyen geolocalización, con lo que no se puede garantizar la ubicación de todos los tweets.  
dc.datacite.formatedDate
2020