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Dataset on usage and engagement patterns for Facebook Live sellers in Thailand

This article describes a Comma Separated Values (CSV) dataset consisting of 7050 Facebook posts of various types (text, deferred and live videos, images). These posts were extracted from the Facebook pages of 10 Thai fashion and cosmetics retail sellers from March 2012, to June 2018. The dataset was...

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Detalles Bibliográficos
Autor principal: Dehouche, Nassim
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7218155/
https://www.ncbi.nlm.nih.gov/pubmed/32420434
http://dx.doi.org/10.1016/j.dib.2020.105661
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author Dehouche, Nassim
author_facet Dehouche, Nassim
author_sort Dehouche, Nassim
collection PubMed
description This article describes a Comma Separated Values (CSV) dataset consisting of 7050 Facebook posts of various types (text, deferred and live videos, images). These posts were extracted from the Facebook pages of 10 Thai fashion and cosmetics retail sellers from March 2012, to June 2018. The dataset was collected via the Facebook API, and anonymized in compliance with the Facebook Platform Policy for Developers [1]. For each Facebook post, the dataset records the resulting engagement metrics comprising shares, comments, and emoji reactions within which we distinguish traditional “likes” from recently introduced emoji reactions, that are “love”, “wow”, “haha”, “sad” and “angry”. This dataset could serve as a basis for research on customer engagement with the novel sales channel that is Facebook Live, through comparative studies with other forms of content (text, deferred videos, and images), as well as the statistical analysis of the seasonality of engagement and outlier posts.
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spelling pubmed-72181552020-05-15 Dataset on usage and engagement patterns for Facebook Live sellers in Thailand Dehouche, Nassim Data Brief Business, Management and Accounting This article describes a Comma Separated Values (CSV) dataset consisting of 7050 Facebook posts of various types (text, deferred and live videos, images). These posts were extracted from the Facebook pages of 10 Thai fashion and cosmetics retail sellers from March 2012, to June 2018. The dataset was collected via the Facebook API, and anonymized in compliance with the Facebook Platform Policy for Developers [1]. For each Facebook post, the dataset records the resulting engagement metrics comprising shares, comments, and emoji reactions within which we distinguish traditional “likes” from recently introduced emoji reactions, that are “love”, “wow”, “haha”, “sad” and “angry”. This dataset could serve as a basis for research on customer engagement with the novel sales channel that is Facebook Live, through comparative studies with other forms of content (text, deferred videos, and images), as well as the statistical analysis of the seasonality of engagement and outlier posts. Elsevier 2020-05-06 /pmc/articles/PMC7218155/ /pubmed/32420434 http://dx.doi.org/10.1016/j.dib.2020.105661 Text en © 2020 The Author(s) http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Business, Management and Accounting
Dehouche, Nassim
Dataset on usage and engagement patterns for Facebook Live sellers in Thailand
title Dataset on usage and engagement patterns for Facebook Live sellers in Thailand
title_full Dataset on usage and engagement patterns for Facebook Live sellers in Thailand
title_fullStr Dataset on usage and engagement patterns for Facebook Live sellers in Thailand
title_full_unstemmed Dataset on usage and engagement patterns for Facebook Live sellers in Thailand
title_short Dataset on usage and engagement patterns for Facebook Live sellers in Thailand
title_sort dataset on usage and engagement patterns for facebook live sellers in thailand
topic Business, Management and Accounting
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7218155/
https://www.ncbi.nlm.nih.gov/pubmed/32420434
http://dx.doi.org/10.1016/j.dib.2020.105661
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