Capturing Tie Strength with Algebraic Topology
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arXiv
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| Auteurs principaux: | , , , |
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| Format: | Preprint |
| Publié: |
2021
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| _version_ | 1866929513761341440 |
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| author | Sarker, Arnab Seby, Jean-Baptiste Benson, Austin R. Jadbabaie, Ali |
| author_facet | Sarker, Arnab Seby, Jean-Baptiste Benson, Austin R. Jadbabaie, Ali |
| contents | The association between tie strength and social structure is a fundamental topic in the social sciences. We study this association by analyzing tie strength in higher-order networks, an increasingly relevant model which can encode group interactions between three or more individuals. First, we introduce three measures based on algebraic topology which characterize the network context and influence of an edge. Our experimental results across 15 datasets indicate that these measures outperform standard network proxies in estimating tie strength. We further find that these measures can replicate and explain a puzzle wherein certain bridging ties are surprisingly strong. We then consider a single centrality measure which combines the three initial measures, is highly inversely related to tie strength, and can be interpreted through an information exchange process which highlights ties that have access to useful information. In this sense, we are able to illuminate the information advantages of weak ties due to their network position. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2108_02091 |
| institution | arXiv |
| publishDate | 2021 |
| record_format | arxiv |
| spellingShingle | Capturing Tie Strength with Algebraic Topology Sarker, Arnab Seby, Jean-Baptiste Benson, Austin R. Jadbabaie, Ali Social and Information Networks Algebraic Topology The association between tie strength and social structure is a fundamental topic in the social sciences. We study this association by analyzing tie strength in higher-order networks, an increasingly relevant model which can encode group interactions between three or more individuals. First, we introduce three measures based on algebraic topology which characterize the network context and influence of an edge. Our experimental results across 15 datasets indicate that these measures outperform standard network proxies in estimating tie strength. We further find that these measures can replicate and explain a puzzle wherein certain bridging ties are surprisingly strong. We then consider a single centrality measure which combines the three initial measures, is highly inversely related to tie strength, and can be interpreted through an information exchange process which highlights ties that have access to useful information. In this sense, we are able to illuminate the information advantages of weak ties due to their network position. |
| title | Capturing Tie Strength with Algebraic Topology |
| topic | Social and Information Networks Algebraic Topology |
| url | https://arxiv.org/abs/2108.02091 |