tag:joss.theoj.org,2005:/papers/reviewed_by/@mkearneyJournal of Open Source Software2019-11-17T18:22:14ZJournal of Open Source Softwarehttps://joss.theoj.orgtag:joss.theoj.org,2005:Paper/10182019-11-17T18:22:14Z2021-02-15T11:32:08Zhopit: An R Package for Analysis of Reporting Behavior Using Generalized Ordered Probit Modelsaccepted0.9.2.90002019-05-28 16:45:51 UTC432019-11-17 18:22:14 UTC420191508MaciejJ.DańkoMax Planck Institute for Demographic Research, Rostock, Germany0000-0002-7924-902210.21105/joss.01508https://doi.org/10.5281/zenodo.3530634R, C++https://joss.theoj.org/papers/10.21105/joss.01508.pdfself-reported status, reporting heterogeneity, reporting behavior, latent index, latent health, disability weightstag:joss.theoj.org,2005:Paper/11752019-10-18T20:13:54Z2021-02-15T11:31:44ZBotSlayer: real-time detection of bot amplification on Twitteracceptedv1.0.02019-08-20 17:59:46 UTC422019-10-18 20:13:54 UTC420191706Pik-MaiHuiCenter for Complex Networks \& Systems Research, Indiana UniversityKai-ChengYangCenter for Complex Networks \& Systems Research, Indiana UniversityChristopherTorres-LugoCenter for Complex Networks \& Systems Research, Indiana UniversityZacharyMonroeCenter for Complex Networks \& Systems Research, Indiana UniversityMarcMcCartyIndiana University Network Science InstituteBenjaminD.SerretteIndiana University Network Science InstituteValentinPentchevIndiana University Network Science InstituteFilippoMenczerCenter for Complex Networks \& Systems Research, Indiana University, Indiana University Network Science Institute10.21105/joss.01706https://doi.org/10.5281/zenodo.3492278Python, JavaScript, Vuehttps://joss.theoj.org/papers/10.21105/joss.01706.pdfTwitter, bot, amplification