Shared Feelings: Understanding Facebook Reactions to Scholarly Articles

Research on social-media platforms has tended to rely on textual analysis to perform research tasks. While text-based approaches have significantly increased our understanding of online behavior and social dynamics, they overlook features on these platforms that have grown in prominence in the past...

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Podrobná bibliografie
Vydáno v:	2019 ACM/IEEE Joint Conference on Digital Libraries (JCDL) s. 301 - 304
Hlavní autoři:	Freeman, Cole, Roy, Mrinal Kanti, Fattoruso, Michele, Alhoori, Hamed
Médium:	Konferenční příspěvek
Jazyk:	angličtina
Vydáno:	IEEE 01.06.2019
Témata:	Altmetrics Data Collection Facebook Reactions Research Community Social Clicks Social Media Analytics Supervised Learning
On-line přístup:	Získat plný text
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Popis
Shrnutí:	Research on social-media platforms has tended to rely on textual analysis to perform research tasks. While text-based approaches have significantly increased our understanding of online behavior and social dynamics, they overlook features on these platforms that have grown in prominence in the past few years: click-based responses to content. In this paper, we present a new dataset of Facebook Reactions to scholarly content. We give an overview of its structure, analyze some of the statistical trends in the data, and use it to train and test two supervised learning algorithms. Our preliminary tests suggest the presence of stratification in the number of users following pages, divisions that seem to fall in line with distinctions in the subject matter of those pages.
DOI:	10.1109/JCDL.2019.00050