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Adjacent binary votes agreed above the expectation from fixed daily counts for 2,290 Wikipedia candidates in 2004–2013

We tested time order in public Wikipedia votes for administrator status. The source was the Netzschleuder wiki_rfa conversion. After date, repeat-record, and size checks, the sample had 118,176 binary votes on 5,954 candidate-days for 2,290 candidates in 2004–2013. Among 109,602 adjacent pairs with clear minute order, agreement was 80.70 percent. The expectation from fixed daily vote counts was 79.58 percent. The excess was 1.12 percentage points. Its descriptive 95 percent candidate bootstrap interval was 0.93 to 1.31 points. No daily null count reached the observed count in 1,999 shuffles. Tests that fixed six-hour and one-hour sign counts gave excesses of 0.54 and 0.29 points on smaller pair sets. A further comparison on the same one-hour pairs gave a daily excess of 1.52 points and an hourly excess of 0.29 points. The result shows that the conditioning time scale matters. It does not identify social influence. Voter selection, common information, missing dates, and shared voters can affect the result. A format audit found that comment quotes can cause a standard CSV reader to merge records. A separate parser recovered all 198,275 source records and checked every output block. The package has code, provenance, aggregate results, random draws, figures, and repeat instructions. The raw source is retained separately and is not relicensed.

Wikipedia · collective decisions · vote order · conditional permutation · data audit · temporal dependence

Admitted 5 citing publications

References

3
  1. usesdoi:10.1162/tacl_a_00184

    This paper is the cited source of the public Wikipedia RfA data. We analyze the Netzschleuder conversion linked to it.

  2. supportsdoi:10.1609/icwsm.v4i1.14013

    Prior work studies public Wikipedia vote sequences and promotion outcomes. It motivates the question. The present work tests local adjacent agreement and does not repeat its outcome test.

  3. supportsdoi:10.1177/0049124111404820

    This paper explains limits on identifying contagion from observational network relations. It supports the stated limit on causal interpretation.

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