Extending the BEND Framework to Webgraphs

Fuente: arXiv
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Main Authors: Williams, Evan M., Carragher, Peter, Herdrich, Kyle, Prakarsa, Luke, Carley, Kathleen M.
Format: Preprint
Published: 2025
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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