The tremendous success of major Online Social Networks (OSNs) platforms has raised increasing concerns about negative phenomena, such as mass control, fake news, and echo chambers. In addition, the increasingly strict control over users’ data by platform owners questions their trustworthiness as open interaction tools. These trends and, notably, the recent drastic change in X (formerly Twitter) policies and data accessibility through public APIs, have fuelled significant migration of users towards Fediverse platforms (primarily Mastodon). In this work, we provide an initial analysis of the microscopic properties of Mastodon users’ social structures. Specifically, according to the Ego network model, we analyse interaction patterns between a large set of users (egos) and the other users they interact with (alters) to characterise the properties of those users’ ego networks. As was observed previously in other OSNs, we found a quite regular structure compatible with the reference Dunbar’s Ego Network model. Quite interestingly, our results show clear signs of ego network formation during the initial diffusion of a social networking tool, coherent with the recent surge of Mastodon activity. Therefore, our analysis motivates the use of Mastodon as an open "big data microscope" to characterise human social behaviour, making it a prime candidate to replace those OSN platforms that, unfortunately, cannot be used anymore for this purpose.

The Ego Network Model (ENM) describes how individuals organise their social relations in concentric circles (typically five) of decreasing intimacy, and it has been found almost ubiquitously in social networks, both offline and online. The ENM gauges the tie strength between peers in terms of interaction frequency, which is easy to measure and provides a good proxy for the time spent nurturing the relationship. However, advances in signed network analysis have shown that positive and negative relations play very different roles in network dynamics. For this reason, this work sets out to investigate the ENM when including signed relations. The main contributions of this paper are twofold: firstly, a novel method of signing relationships between individuals using sentiment analysis and, secondly, an investigation of the properties of Signed Ego Networks (Ego Networks with signed connections). Signed Ego Networks are then extracted for the users of eight different Twitter datasets composed of both specialised users (e.g. journalists) and generic users. We find that negative links are over-represented in the active part of the Ego Networks of all types of users, suggesting that Twitter users tend to engage regularly with negative connections. Further, we observe that negative relationships are overwhelmingly predominant in the Ego Network circles of specialised users, hinting at very polarised online interactions for this category of users. In addition, negative relationships are found disproportionately more at the more intimate levels of the ENM for journalists, while their percentages are stable across the circles of the other Twitter users.