Extending the BEND Framework to Webgraphs
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arXiv
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| Main Authors: | , , , , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | |
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| _version_ | 1866909791603916800 |
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| author | Williams, Evan M. Carragher, Peter Herdrich, Kyle Prakarsa, Luke Carley, Kathleen M. |
| author_facet | Williams, Evan M. Carragher, Peter Herdrich, Kyle Prakarsa, Luke Carley, Kathleen M. |
| contents | Attempts to manipulate webgraphs can have many downstream impacts, but analysts lack shared quantitative metrics to characterize actions taken to manipulate information environments at this level. We demonstrate how the BEND framework can be used to characterize attempts to manipulate webgraph information environments, and propose quantitative metrics for BEND community maneuvers. We demonstrate the face validity of our proposed Webgraph BEND metrics by using them to characterize two small web-graphs containing SEO-boosted Kremlin-aligned websites. We demonstrate how our proposed metrics improve BEND scores in webgraph settings and demonstrate the usefulness of our metrics in characterizing webgraph information environments. These metrics offer analysts a systematic and standardized way to characterize attempts to manipulate webgraphs using common Search Engine Optimization tactics. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2509_13212 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Extending the BEND Framework to Webgraphs Williams, Evan M. Carragher, Peter Herdrich, Kyle Prakarsa, Luke Carley, Kathleen M. Social and Information Networks Attempts to manipulate webgraphs can have many downstream impacts, but analysts lack shared quantitative metrics to characterize actions taken to manipulate information environments at this level. We demonstrate how the BEND framework can be used to characterize attempts to manipulate webgraph information environments, and propose quantitative metrics for BEND community maneuvers. We demonstrate the face validity of our proposed Webgraph BEND metrics by using them to characterize two small web-graphs containing SEO-boosted Kremlin-aligned websites. We demonstrate how our proposed metrics improve BEND scores in webgraph settings and demonstrate the usefulness of our metrics in characterizing webgraph information environments. These metrics offer analysts a systematic and standardized way to characterize attempts to manipulate webgraphs using common Search Engine Optimization tactics. |
| title | Extending the BEND Framework to Webgraphs |
| topic | Social and Information Networks |
| url | https://arxiv.org/abs/2509.13212 |