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Extending the BEND Framework to Webgraphs

delete2026-01-01
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PRE
AI
E
Evan M. Williams *
P
Peter Carragher
K
Kyle Herdrich
L
Luke Prakarsa
K
Kathleen M. Carley
DOI:10.1007/978-3-032-07715-8_8delete
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Abstract

Abstract

En 中文
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 SEOboosted 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.
Keywords:
Web Graphs
Search Engine Optimization
SEO
BEND
Information Operations

Journal

S
SOCIAL, CULTURAL, AND BEHAVIORAL MODELING, SBP-BRIMS 2025
IF:
0
Papers:
21
Citations:
0

Organization

C
carnegie mellon university
Scholars:
1.9K
Papers: 937
Citations: 0