Keep Your Friends Close, and Your Enemies Closer: Structural Properties of Negative Relationships on Twitter
CoRR(2024)
摘要
The Ego Network Model (ENM) is a model for the structural organisation of
relationships, rooted in evolutionary anthropology, that is found ubiquitously
in social contexts. It takes the perspective of a single user (Ego) and
organises their contacts (Alters) into a series of (typically 5) concentric
circles of decreasing intimacy and increasing size. Alters are sorted based on
their tie strength to the Ego, however, this is difficult to measure directly.
Traditionally, the interaction frequency has been used as a proxy but this
misses the qualitative aspects of connections, such as signs (i.e. polarity),
which have been shown to provide extremely useful information. However, the
sign of an online social relationship is usually an implicit piece of
information, which needs to be estimated by interaction data from Online Social
Networks (OSNs), making sign prediction in OSNs a research challenge in and of
itself. This work aims to bring the ENM into the signed networks domain by
investigating the interplay of signed connections with the ENM. This paper
delivers 2 main contributions. Firstly, a new and data-efficient method of
signing relationships between individuals using sentiment analysis and,
secondly, we provide an in-depth look at the properties of Signed Ego Networks
(SENs), using 9 Twitter datasets of various categories of users. We find that
negative connections are generally over-represented in the active part of the
Ego Networks, suggesting that Twitter greatly over-emphasises negative
relationships with respect to "offline" social networks. Further, users who use
social networks for professional reasons have an even greater share of negative
connections.
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