SpanishTweetsCOVID-19: A Social Media Enriched Covid-19 Twitter Spanish Dataset

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Título

SpanishTweetsCOVID-19: A Social Media Enriched Covid-19 Twitter Spanish Dataset

Autor(es)

Tommasel, Antonela

Afiliación(es) del/de los autor(es)

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

Resumen

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.

Año de publicación

2023

Idioma

español

Formato (Tipo MIME)

application/octet-stream
application/zip
application/vnd.rar

Clasificación temática de acuerdo a la FORD

Ciencias informáticas y de la información

Condiciones de uso

Disponible en acceso abierto bajo licencia Creative Commons https://creativecommons.org/licenses/by-nc-sa/2.5/ar/

Repositorio digital

CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas

Identificador de proyecto

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