Facebook Posts, Comments, Likes, & Shares

What it is

Facebook posts, comments, likes and shares refer to user-generated actions in Facebook that can be aggregated and represented quantitatively when associated with a unique URL. Any research output with a unique URL can thus be tracked for the number of Facebook user interactions it generates in these categories over time.

How it works

A post is counted when a Facebook user shares the unique link. A comment is counted when a user submits text beneath the post that includes the unique link. A like is counted when a user clicks the “like” option beneath the post that includes the unique link. A share is counted when a user chooses the option to share the original post that includes the unique link, e.g. with users in their own Facebook network.

Facebook data on posts, comments, likes and shares are collected and parsed by altmetrics aggregators including Altmetric, ImpactStory, and PlumX. Data is also available to and auditable by individual users using the Facebook Graph API.

What to keep in mind

  • Aggregators differ in how they collect Facebook data, and in transparency. Different altmetric aggregators have slightly different ways of calculating Facebook metrics. For instance, Altmetric and ImpactStory (which share the same altmetric data) only count interactions with public posts linking to research outputs, while PlumX counts both interactions with public posts and private interactions that have been anonymized via the Facebook Graph API. While this difference means Altmetrics and Impactstory track only a fraction of Facebook activity for research, it also means that PlumX’s counts of private Facebook interactions cannot be independently audited for context or accuracy.
  • Many research outputs have more than one URL. Research outputs with more than one associated URL are difficult to track accurately on Facebook, as the API is built around tracking Facebook interactions with one URL at a time. Facebook metrics also do not capture posts that discuss a research output (e.g. by title or author) but do not include an associated URL, or that link to a peripheral URL like an output author’s professional profile.
  • Facebook interactions measure engagement, not impact or quality. Facebook-based indicators should not be used as a predictive indicator of future citations, and they should not be used as measures of scientific quality or impact. Multiple studies on the scholarly use of social media have found that the correlation between Facebook metrics and article citations is weak, which suggests Facebook posts, comments, likes, and shares may evidence different or less formal kinds of interest and use of scholarship.
  • Highly aggregated counts make it difficult to interpret Facebook engagement. While posts, comments, likes and shares are each unique forms of engagement on the Facebook platform, their counts are sometimes combined by data providers, which makes meaningful interpretation of Facebook indicators more difficult.

Learn more

  • Facebook for Developers
  • Facebook Graph API
  • Sugimoto, C. R., Work, S., Larivière, V., & Haustein, S. (2017). Scholarly use of social media and altmetrics: A review of the literature. Journal of the Association for Information Science and Technology, 68(9), 2037–2062. https://doi.org/10.1002/asi.23833
  • Zahedi, Z., & Costas, R. (2018). General discussion of data quality challenges in social media metrics: Extensive comparison of four major altmetric data aggregators. PLoS ONE, 13(5), e0197326. https://doi.org/10.1371/journal.pone.0197326

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Last updated April 2022