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Reproducibility, Replicability, and Revisiting the Insta-Dead and the Human Remains TradeOpen Materials

Shawn Graham and Damien Huffer

Cite this as: Graham, S. and Huffer, D. 2020 Reproducibility, Replicability, and Revisiting the Insta-Dead and the Human Remains Trade, Internet Archaeology 55. https://doi.org/10.11141/ia.55.11

Summary

Photos retrieved from a simple search of Instagram for 'Human Skulls',  collected July 10 2017
Photos retrieved from a simple search of Instagram for 'Human Skulls', collected July 10 2017

The trade in human remains on social media happens in an ever-changing field of digital media technologies. We attempt to replicate our earlier study, exploring the differences in what we can observe now in the trade on Instagram versus our first foray in 2016 (published in Huffer and Graham 2017). While the previous study cannot be reproduced, it can be replicated, and we find that the trade is accelerating.

Corresponding author: Shawn GrahamORCID logo
ShawnGraham@cunet.carleton.ca
Carleton University

Co-author: Damien HufferORCID logo
Carleton University

Full text

Figure 1: Social network visualisation of the filtered network of 70 accounts that named a price in posts made in 2020; the unfiltered network consists of 235,593 accounts connected by 257,676 'follower' relationships at one step. Colour is assigned through community detection (nodes that have similar patterns of relationships are assigned to the same cluster and coloured accordingly). There is a central 'core' group of vendors who are connected together, while there is a large penumbra of 'one off' accounts that from this perspective have nothing to do with each other

Figure 2: Social network visualisation of the same data (235,593 accounts connected by 257,676 edges) recast so that the 70 vendors are connected to each other by virtue of having followers in common (a person that follows vendor A and also follows vendor B is turned into an edge or tie between A and B; each edge thus has a 'weight' that represents the number of followers in common). A vendor might not follow another vendor (as in that 'penumbra' depicted in Figure 1) but be connected by having followers in common: thus for those followers the two vendors' posts help create a culture of consumption around images of human remains (which may or may not lead to purchases). Community detection is run again, taking edge weight into account. The result is three distinct groups.

Figure 3: Dendrogram of word vector distances illustrating the vector space around the word 'legal' in word posts.

Figure 4: Dendrogram of topic similarities in a 25 topic topic-model of the posts.

Table 1: Seed hashtags

Table 2: Expanded seed hashtags

Table 3: Annual sales figures in Instagram posts collected in September 2020 where the vendor was bold enough to state a price. Note that these figures necessarily understate the total volume of sales, and so should be taken to indicate a trajectory, rather than absolute values. Also note that the 2020 values only represent the first three quarters of the year's volume

Table 4: Annual sales figures in Instagram posts where the vendor was bold enough to state a price from our earlier study (Huffer and Graham 2017)

Table 5: The twenty most frequent hashtags in scraped posts, 2020

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