Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-12T13:22:27.717725Z
Paper Citation Record · LEDGER
As of 13 August 2026, this Paper Citation Record lists 75 of 75 outbound references and 0 inbound Pith citation observations for arXiv:2411.16285.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-12T13:22:27.717725Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
75 of 75 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation 677127ba-b10b-49a0-8245-37bb2d88a917 · outbound
A Graph Neural Architecture Search Approach for Identifying Bots in Social Media Multitask learning for recognizing stress and depression in social media
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A Graph Neural Architecture Search Approach for Identifying Bots in Social Media Social bots distort the 2016 u.s
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A Graph Neural Architecture Search Approach for Identifying Bots in Social Media What types of covid-19 conspiracies are populated by twitter bots? First Monday, 5 2020
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A Graph Neural Architecture Search Approach for Identifying Bots in Social Media Dialog in the echo chamber: Fake news framing predicts emotion, argumentation and dialogic social knowledge building in subsequent online discussions
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A Graph Neural Architecture Search Approach for Identifying Bots in Social Media Twitter bot detection using diverse content features and applying ma- chine learning algorithms
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A Graph Neural Architecture Search Approach for Identifying Bots in Social Media Bot-mgat: A transfer learning model based on a multi-view graph attention network to detect social bots
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A Graph Neural Architecture Search Approach for Identifying Bots in Social Media Satar: A self-supervised approach to twitter account representation learning and its application in bot detection
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A Graph Neural Architecture Search Approach for Identifying Bots in Social Media Multi-view co- attention network for fake news detection by modeling topic-specific user and news source credibility
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A Graph Neural Architecture Search Approach for Identifying Bots in Social Media Detecting bots in social-networks using node and structural embeddings
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Reference 73
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No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation d711ef06-f00a-4311-8fc8-3b455c0f3c04 · outbound
A Graph Neural Architecture Search Approach for Identifying Bots in Social Media Unresolved cited work
Reference 2019
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 13fd3247-bc17-4f68-a523-b0c1bbd674a1 · outbound
A Graph Neural Architecture Search Approach for Identifying Bots in Social Media Unresolved cited work
Reference 2023
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
No inbound Pith citation observations are available.