Signed ego network model and its application to Twitter

TL;DR

This paper extends the Ego Network Model to signed relations on Twitter, revealing that negative ties are prevalent and more prominent in the inner circles, especially among specialized users like journalists.

Contribution

It introduces a sentiment-based method for signing relationships and analyzes the properties of Signed Ego Networks in Twitter, highlighting the role of negative ties.

Findings

Negative links are over-represented in active Ego Networks.

Negative relationships dominate in specialized users' Ego Network circles.

Negative ties are more common at intimate levels for journalists.

Abstract

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