Into the Dark: A Case Study of Banned Darknet Drug Forums

Abstract

In March 2018, to the surprise of many users, the largest Reddit forums related to darknet markets (DNM) were banned overnight. For users, whose trading activity relied heavily on these forums, the ban was a threat to the community as a whole. In this study we use a complete set of posts from the newly founded forums in the darknet-based “Dread” platform to examine key discussion topics and the sentiment of the community towards the ban. We look at the level of user engagement in the new forums, and the number of users who retain their old usernames. Applying topic modelling to posts on the new forum, we show that there are many overlapping themes across both the banned and new forums, and that discussions on drugs are the most prominent, followed by vendors, shipping reviews, and payment methods. We observe that the new community demonstrates negative sentiment toward the unexpected ban and the loss of accumulated information, but also holds a favourable view of Dread in the hopes that it will offer greater features and security for the users. Users across both platforms express attachment and affinity to the general DNM community, and demonstrate relation to it beyond the commercial purpose.

A Appendices

1.1 A.1 Timeline of the number of postings

Forums were banned intermittently prior to March as seen by a gradual drop since December in Fig. 1. May’s sudden drop is when the platform had a brief downtime. Reddit provided a much richer variety of DNM-related forums specialising in specific drugs and countries, and such details had not yet transferred over to Dread, including popular market forums as Agora, TradeRoute, and TheMajesticGarden. Reddit potentially had more passer-bys who subscribed to the forums out of fleeting curiosity, without intending to access the DNM themselves.

Fig. 1.

Number of postings over the months (2017–2018) overlapping the ban

1.2 A.2 Document Word Counts

See Fig. 2.

Fig. 2.

Distribution of the word counts in documents to which the LDA was applied

1.3 A.3 Perplexity

In Fig. 3b, we obtained a string of negative bound values ranging between −8.115 and −8.150. Even though a lower perplexity is desired, the value likely denotes deterioration of the sample data from infinitesimal probabilities being converted to the log scale by Gensim. As a result, we found the number of topics for Dread by inspection rather than relying on the perplexity per se.

Fig. 3.

Perplexity results when run up to 15 topics

1.4 A.4 Histogram of Polarity

See Fig. 4 for the histogram of the polarity seen in Reddit and Dread. The common threshold of $-0.1<$ x $<0.1$ for neutral gave an abnormally high level of positive sentiments, which weren’t always the case upon inspection of the original posts by the authors, with 391 positive, 61 negative, and 299 neutral categories. To suit the histogram fit better, we adjusted the threshold upwards to $-0.001<$ x $<1.999$ for the neutral category.

Fig. 4.

Histogram showing the probability of polarity rate

1.5 A.5 Extended Posts from Sentiment Analysis

Table 7 shows posts with positive or negative sentiments, from Sect. 4.2. Table 8 shows posts with mixed sentiments.

Table 7. Extended posts with positive or negative sentiments from Sect. 4.2.

Table 8. Posts with mixed sentiment rating.

1.6 A.6 Proportion of the User Engagement

See Table 9 to see the proportion of user engagement. As mentioned in the methodology, multiple Reddit forums corresponded to a same Dread forum, and so we accumulated the alternative forums to reflect the average number of user engagement across different forums that had appeared in the forum’s posts.

Table 9. The proportion (%) of user engagement by subscription rate, based on the list of main banned subreddits and its equivalent forums present in Dread, alongside the number of subscribers (S) per forum and the number of unique usernames (N).