Wash trading is considered a highly inopportune and illegal behavior in regulated markets. Instead, it is practiced in unregulated markets, such as cryptocurrency or NFT (Non-Fungible Tokens) markets. Regarding the latter, in the past many researchers have been interested in this phenomenon from an “ex-ante” perspective, aiming to identify and classify wash trading activities before or at the exact time they happen. In this paper, we want to investigate the phenomenon of wash trading in the NFT market from a completely different perspective, namely “ex-post”. Our ultimate goal is to analyze wash trading activities in the past to understand whether the game is worth the candle, i.e., whether these illicit activities actually lead to a significant profit for their perpetrators. To the best of our knowledge, this is the first paper in the literature that attempts to answer this question in a “structured” way. The efforts to answer this question have enabled us to make some additional contributions to the literature in this research area. They are: (i) a framework to support future “ex-post” analyses of the NFT wash trading phenomenon; (ii) a new dataset on wash trading transactions involving NFTs that can support further future investigations of this phenomenon; (iii) a set of insights of the NFT wash trading phenomenon extracted at the end of an experimental campaign.

The concept of scope was introduced in Social Network Analysis to assess the authoritativeness and convincing ability of a user toward other users on one or more social platforms. It has been studied in the past in some specific contexts, for example to assess the ability of a user to spread information on Twitter. In this paper, we propose a new investigation on scope, as we want to assess the scope of the sentiment of a user on a topic. We also propose a multi-dimensional definition of scope. In fact, besides the traditional spatial scope, we introduce the temporal one, which has never been addressed in the literature, and propose a model that allows the concept of scope to be extended to further dimensions in the future. Furthermore, we propose an approach and a related set of parameters for measuring the scope of the sentiment of a user on a topic in a social network. Finally, we illustrate the results of an experimental campaign we conducted to evaluate the proposed framework on a dataset derived from Reddit. The main novelties of this paper are: (i) a multi-dimensional view of scope; (ii) the introduction of the concept of sentiment scope; (iii) the definition of a general framework capable of analyzing the sentiment scope related to any subject on any social network.

In just few years, TikTok has become a major player in the social media environment, especially with regard to teenagers. One of the key factors of this success is the idea of challenges, that is, video competitions/emulations on a certain topic, which a user can launch and other ones can join. Most of the challenges are fun and harmless. However, there are also users who launch challenges that are dangerous, or at least suitable only for an adult audience (and TikTok is the most popular social network for teenagers). This article focuses primarily on this kind of challenge. In particular, it investigates an aspect not yet studied in the literature, which is the different characteristics and evolutionary dynamics of the communities of users participating in non-dangerous and dangerous challenges. Its final goal is the identification of evolutionary patterns that distinguish the communities of users participating in the two types of challenges. The knowledge of these patterns could be a first step in implementing an approach to the early detection of dangerous challenges in TikTok.

A simplified method to compute $$R_t$$R t , the effective reproduction number, is presented. The method relates the value of $$R_t$$R t to the estimation of the doubling time performed with a local exponential fit. The condition $$R_t=1$$R t = 1 corresponds to a growth rate equal to zero or equivalently an infinite doubling time. Different assumptions on the probability distribution of the generation time are considered. A simple analytical solution is presented in case the generation time follows a gamma distribution.