Digging in to the validity of this analysis myself - some say its an OK method for detecting election fraud, but others disagree. See this research paper as a counterexample: https://www.cambridge.org/core/services/aop-cambridge-core/content/view/3B1D64E822371C461AF3C61CE91AAF6D/S1047198700012808a.pdf/benfords_law_and_the_detection_of_election_fraud.pdf
If anyone has more proof in favor of, please share as it is an interesting topic. Just count on it being contested if it goes to court.
Edit:
Above article is interesting reading - some other items to look for in these data sets:
A second example illustrates a less formal type of theory we deem essential for evaluating any proposed forensic indicator of fraud. We refer here to the argument of Berber and Scacco (2008) for the relevance of looking at the last and next to last digits of vote tallies. They begin by noting that if there is little chance that the perpetrators of fraud fear prosecution even if detected (as is the case in contemporary Russia), it is not unreasonable to be suspicious of precinct or regional tallies that report a proportion of zeros and fives as the last digit in excess of what we expect by chance. Their ‘‘theory’’ here is simply the supposition that absent any legal disincentives for committing fraud, precinct and local election officials can meet their ‘‘quotas’’ and save effort by employing the simple heuristic of rounding off the numbers they report, presumably without regard to actual ballots cast. Indeed, it is precisely rounding of this sort that one finds in abundance in the turnout numbers of Russia’s 2004 and 2008 presidential elections (Buzin and Lubarev 2008).
Berber and Scacco, though, also confront the possibility that fraud’s perpetrators will seek to disguise their actions, and here they note that if perpetrators attempt to do so by entering what they regard as random (but nevertheless, manipulated) numbers in official tallies, there is a considerable body of experimental evidence in behavioral economics to suggest (as a parallel to the Joseph Deckert et al. gambler’s fallacy) they will write repeated digits less frequently than what we expect by chance (Camerer 2003). That is, protocol entries ending with the digits ‘‘00,’’ ‘‘11,’’ ‘‘22,’’ and so on should, in a fraud free election, occur a tenth of the time, and it is reasonable to be suspicious of protocols if observed frequencies are significantly less than this fraction (for the application of this test to a suspect election see Levin et al. 2009).
Digging in to the validity of this analysis myself - some say its an OK method for detecting election fraud, but others disagree. See this research paper as a counterexample: https://www.cambridge.org/core/services/aop-cambridge-core/content/view/3B1D64E822371C461AF3C61CE91AAF6D/S1047198700012808a.pdf/benfords_law_and_the_detection_of_election_fraud.pdf
If anyone has more proof in favor of, please share as it is an interesting topic. Just count on it being contested if it goes to court.