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Constructing an Artworld Influencers Network by Mining Social Media

The author shows a methodology for constructing a network map of the artworld.

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Why am I seeing this Ranked on recency

It is here mostly because it is new. Freshness is the largest single contributor to its score, which means nothing about the story except that it is recent.

Nothing much is corroborating this yet. On a quiet day in streaming that is enough to reach the top of the section — recency, not significance, is doing the work here.

Link-outLink-out, because it scores 0.45, below the 0.50 bar for a write-up. Link-out means we point at the publisher and say nothing of our own.

Blended score 0.450 — every figure below is computed, none of it is editorial.
FactorWeightScore ContributionWhere it came from
Corroboration 0.35 0.39 +0.135 30% 1 independent org on the story. Tier-3 aggregators never corroborate — they can show something is circulating, never that it is true.
Source trust 0.25 0.47 +0.117 26% arXiv is the highest-trust source on this story and is first-party — the organisation announcing its own news. Trust is taken from the best source, not averaged.
Pickup rate 0.20 0.00 +0.000 0% One counted organisation, so there is no spread to measure — nothing has picked this up to set a rate.
Freshnessleads 0.20 0.99 +0.198 44% Halves every 10 hours from the newest item on the story. This is the only factor that rewards a story for nothing more than being recent.

Corroboration counts distinct organisations, once each, and only from tiers 1 and 2. Freshness halves every 10 hours, so this ranking is a snapshot and will differ at the next build.

Read the full article at Arxiv →

What happened

The author shows a methodology for constructing a network map of the artworld. The tweets posted by a manually comprised set of exemplar artworld actors and Natural Language Processing (NLP) methods are used to identify significant artworld actors, including those that do not own a Twitter account. Identified artworld actors form communities detected with the Louvain method, and their authority is evaluated with the HITS centrality method. The resulting artworld network exhibits the ability, starting with a small set of exemplar actors, to identify new artworld actors and provides a wealth of data that would be very hard to collect otherwise.

1independent orgs
20story score
0velocity
47source trust
1passes seen

How this story arrived

Ordered by when each source was first observed, which is what the velocity figure is computed from. Publishers backdate; observed order does not.

  1. 01 Arxivfirst-party first seen Constructing an Artworld Influencers Network by Mining Social Media

Overclock clusters coverage from independent sources and grades it automatically. The figures above are computed, not editorial. This page summarises and links to reporting by the outlets named — follow the links for the original work.