A criticism to Society (as seen by Twitter analytics) (Rapporti tecnici, manuali, carte geologiche e tematiche e prodotti multimediali)

Type
Label
  • A criticism to Society (as seen by Twitter analytics) (Rapporti tecnici, manuali, carte geologiche e tematiche e prodotti multimediali) (literal)
Anno
  • 2014-01-01T00:00:00+01:00 (literal)
Alternative label
  • Stefano Cresci, Roberto Di Pietro, Marinella Petrocchi, Angelo Spognardi, Maurizio Tesconi (2014)
    A criticism to Society (as seen by Twitter analytics)
    (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
  • Stefano Cresci, Roberto Di Pietro, Marinella Petrocchi, Angelo Spognardi, Maurizio Tesconi (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#supporto
  • Altro (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
  • IIT-CNR (literal)
Titolo
  • A criticism to Society (as seen by Twitter analytics) (literal)
Abstract
  • Analytic tools are beginning to be largely employed, given their ability to rank, e.g., the visibility of social media users. Visibility that, in turns, can have a monetary value, since social media popular people usually either anticipate or establish trends that could impact the real world (at least, from a consumer point of view). The above rationale has fostered the flourishing of private companies providing statistical results for social media analysis. These results have been accepted, and largely diffused, by media without any apparent scrutiny, while Academia has moderately focused its attention on this phenomenon. In this paper, we provide evidence that analytic results provided by field-flagship companies are questionable (at least). In particular, we focus on Twitter and its \"fake followers\". We survey popular Twitter analytics that count the fake followers of some target account. We perform a series of experiments aimed at verifying the trustworthiness of their results. We compare the results of such tools with a machine-learning classifier whose methodology bases on scientific basis and on a sound sampling scheme. The findings of this work call for a serious re-thinking of the methodology currently used by companies providing analytic results, whose present deliveries seem to lack on any reliability. (literal)
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