{"title":"Catch Me if You Can: Using a Threshold Model to Simulate Support for Presidential Candidates in the Invisible Primary","authors":"E. Stiles, C. Swearingen, L. Seiter, B. Foreman","doi":"10.18564/jasss.4158","DOIUrl":null,"url":null,"abstract":"The invisible primary is an important time inUnitedStatesPresidential primarypolitics as candidates gainmomentum for their campaigns before they compete formally in the first state caucus (Iowa) andprimaries (e.g. NewHampshire). This critical period has not been possible to observe, hence the name. However, by simulating networks of primary followers, we can explicate hypotheses for howmessages travel through networks to a ect voter preferences. To do so, we use a threshold model to drive our simulated network analysis testing spread of public support for candidates in invisible primaries. We assign voter thresholds for candidates and vary number of voters, attachment to candidates and decay. We also vary social graph structure and model. Results of the algorithm show e ects of size of lead, an unwavering base of support, and information loss.","PeriodicalId":14675,"journal":{"name":"J. Artif. Soc. Soc. Simul.","volume":"1 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2020-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"J. Artif. Soc. Soc. Simul.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.18564/jasss.4158","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
The invisible primary is an important time inUnitedStatesPresidential primarypolitics as candidates gainmomentum for their campaigns before they compete formally in the first state caucus (Iowa) andprimaries (e.g. NewHampshire). This critical period has not been possible to observe, hence the name. However, by simulating networks of primary followers, we can explicate hypotheses for howmessages travel through networks to a ect voter preferences. To do so, we use a threshold model to drive our simulated network analysis testing spread of public support for candidates in invisible primaries. We assign voter thresholds for candidates and vary number of voters, attachment to candidates and decay. We also vary social graph structure and model. Results of the algorithm show e ects of size of lead, an unwavering base of support, and information loss.