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Data from: The viewer doesn’t always seem to care - response to fake animal rescues on YouTube and implications for social media self-policing policies

Cite this dataset

Harrington, Lauren; Elwin, Angie; Patterson, Suzi; D'Cruze, Neil (2022). Data from: The viewer doesn’t always seem to care - response to fake animal rescues on YouTube and implications for social media self-policing policies [Dataset]. Dryad.


Animal-related content on social media is hugely popular but is not always appropriate in terms of how animals are portrayed or how they are treated. This has potential implications beyond the individual animals involved, for viewers, for wild animal populations, and for societies and their interactions with animals. Whilst social media platforms usually publish guidelines for permitted content, enforcement relies at least in part on viewers reporting inappropriate posts. Currently, there is no external regulation of social media platforms. Based on a set of 241 "fake animal rescue" videos that exhibited clear signs of animal cruelty and strong evidence of being deliberately staged (i.e. fake), we found little evidence that viewers disliked the videos and an overall mixed response in terms of awareness of the fake nature of the videos, and their attitudes towards the welfare of the animals involved. Our findings suggest, firstly, that despite the narrowly defined nature of the videos used in this case study, exposure rates can be extremely high (one of the videos had been viewed over 100 million times), and, secondly, that many YouTube viewers cannot identify (or are not concerned by) animal welfare or conservation issues within a social media context. In terms of the current policy approach of social media platforms, our findings raise questions regarding the value of their current reliance on consumers as watch dogs.


Data collection

The dataset pertains to 241YouTube videos identified using the search function in YouTube and the search terms "primitive man saves" and "primitive boy saves" between May and July 2021; supplemented with additional similar videos held in a database collated by Animals for Asia ( Video metrics were extracted automatically between 24.06.21 and 02.08.21 using the "tuber" package in R (Sood 2020, ). Additional information (e.g. on animal taxa) was obtained manually by screening the videos. For five of the videos that received > 1,000 comments, comment text was also extracted using the tuber package. Only publicly available videos were accessed.  

Data processing

Users (video posters and commenters) have been de-identified. For each video for which comment text was analysed, the text was converted into a list of the most frequently used words and emojis. Please refer to the manuscript for further details on the methods and approach used to identify and define the most frequently used words/emojis, and to assign sentiment scores.

Usage notes

The dataset is in .xlsx format and contains four sheets:

1. A description of the variables in the other sheets

2. YouTube videos and associated metrics

3. The most frequently occuring words in the comment text

4. The most frequently occuring emojis in the comment text


World Animal Protection