Keep your friends close, and your enemies closer: structural properties of negative relationships on Twitter
Abstract 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) c...
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SpringerOpen
2024-08-01
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| Series: | EPJ Data Science |
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| Online Access: | https://doi.org/10.1140/epjds/s13688-024-00485-y |
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| author | Jack Tacchi Chiara Boldrini Andrea Passarella Marco Conti |
| author_facet | Jack Tacchi Chiara Boldrini Andrea Passarella Marco Conti |
| author_sort | Jack Tacchi |
| collection | DOAJ |
| description | Abstract 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. Despite this, we also found weak signs that less negative users tend to allocate more cognitive effort to individual relationships and thus have smaller ego networks on average. All in all, even though structurally ENMs are known to be similar in both offline and online social networks, our results indicate that relationships on Twitter tend to nurture more negativity than offline contexts. |
| format | Article |
| id | doaj-art-72663a11bcaa43fcb31f7ff6217ee08e |
| institution | Kabale University |
| issn | 2193-1127 |
| language | English |
| publishDate | 2024-08-01 |
| publisher | SpringerOpen |
| record_format | Article |
| series | EPJ Data Science |
| spelling | doaj-art-72663a11bcaa43fcb31f7ff6217ee08e2025-01-26T12:20:02ZengSpringerOpenEPJ Data Science2193-11272024-08-0113114710.1140/epjds/s13688-024-00485-yKeep your friends close, and your enemies closer: structural properties of negative relationships on TwitterJack Tacchi0Chiara Boldrini1Andrea Passarella2Marco Conti3Consiglio Nazionale delle RicercheConsiglio Nazionale delle RicercheConsiglio Nazionale delle RicercheConsiglio Nazionale delle RicercheAbstract 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. Despite this, we also found weak signs that less negative users tend to allocate more cognitive effort to individual relationships and thus have smaller ego networks on average. All in all, even though structurally ENMs are known to be similar in both offline and online social networks, our results indicate that relationships on Twitter tend to nurture more negativity than offline contexts.https://doi.org/10.1140/epjds/s13688-024-00485-yOnline Social NetworksEgo Network ModelSigned networksSigned Ego Network ModelTwitter |
| spellingShingle | Jack Tacchi Chiara Boldrini Andrea Passarella Marco Conti Keep your friends close, and your enemies closer: structural properties of negative relationships on Twitter EPJ Data Science Online Social Networks Ego Network Model Signed networks Signed Ego Network Model |
| title | Keep your friends close, and your enemies closer: structural properties of negative relationships on Twitter |
| title_full | Keep your friends close, and your enemies closer: structural properties of negative relationships on Twitter |
| title_fullStr | Keep your friends close, and your enemies closer: structural properties of negative relationships on Twitter |
| title_full_unstemmed | Keep your friends close, and your enemies closer: structural properties of negative relationships on Twitter |
| title_short | Keep your friends close, and your enemies closer: structural properties of negative relationships on Twitter |
| title_sort | keep your friends close and your enemies closer structural properties of negative relationships on twitter |
| topic | Online Social Networks Ego Network Model Signed networks Signed Ego Network Model |
| url | https://doi.org/10.1140/epjds/s13688-024-00485-y |
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