[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"detail-sidebar-cat-0-en-105":3,"doc-seo-290440-105":59,"doc-detail-290440-en":131},{"code":4,"msg":5,"data":6},0,"success",[7,13,18,23,28,33,38,43,48,51,55],{"id":8,"doc_module":4,"doc_module_name":9,"category_name":10,"show_sort_weight":11,"slug":12},1,"Document","Story & Novel",90,"story-novel",{"id":14,"doc_module":4,"doc_module_name":9,"category_name":15,"show_sort_weight":16,"slug":17},2,"Literature",80,"literature",{"id":19,"doc_module":4,"doc_module_name":9,"category_name":20,"show_sort_weight":21,"slug":22},4,"Exam",70,"exam",{"id":24,"doc_module":4,"doc_module_name":9,"category_name":25,"show_sort_weight":26,"slug":27},5,"Comic",60,"comic",{"id":29,"doc_module":4,"doc_module_name":9,"category_name":30,"show_sort_weight":31,"slug":32},6,"Technology",50,"technology",{"id":34,"doc_module":4,"doc_module_name":9,"category_name":35,"show_sort_weight":36,"slug":37},7,"Healthcare",40,"healthcare",{"id":39,"doc_module":4,"doc_module_name":9,"category_name":40,"show_sort_weight":41,"slug":42},8,"Research & Report",30,"research-report",{"id":44,"doc_module":4,"doc_module_name":9,"category_name":45,"show_sort_weight":46,"slug":47},9,"Religion & Spirituality",20,"religion-spirituality",{"id":46,"doc_module":4,"doc_module_name":9,"category_name":49,"show_sort_weight":46,"slug":50},"World Cup","world-cup",{"id":52,"doc_module":4,"doc_module_name":9,"category_name":53,"show_sort_weight":52,"slug":54},10,"Lifestyle","lifestyle",{"id":56,"doc_module":4,"doc_module_name":9,"category_name":57,"show_sort_weight":24,"slug":58},19,"General","general",{"code":4,"msg":60,"data":61},"ok",{"site_id":62,"language":63,"slug":64,"title":65,"keywords":66,"description":67,"schema_data":68,"social_meta":124,"head_meta":126,"extra_data":128,"updated_unix":130},105,"en","predicting-party-switching-through-machine-learning-and-open-data","Predicting party switching through machine learning and open data","","Party switching among legislators is common and can disrupt parliamentary power balances, electoral outcomes, and democratic stability. The article develops a machine-learning algorithm to forecast party switching in the Italian Parliament using open legislative voting data. Analysis of voting records from the XVII (2013–2018) and XVIII (2018–2022) legislatures shows party switchers participate more often in secret ballots and steadily decrease alignment with their party’s majority votes up to two months before switching. Prediction reaches over 70% accuracy.",{"@graph":69,"@context":123},[70,84,106],{"@type":71,"itemListElement":72},"BreadcrumbList",[73,77,79,82],{"item":74,"name":75,"@type":76,"position":8},"https://docshare.wps.com","Home","ListItem",{"item":78,"name":9,"@type":76,"position":14},"https://docshare.wps.com/document/",{"item":80,"name":40,"@type":76,"position":81},"https://docshare.wps.com/document/research-report/",3,{"item":83,"name":65,"@type":76,"position":19},"https://docshare.wps.com/document/predicting-party-switching-through-machine-learning-and-open-data/290440/",{"url":83,"name":65,"@type":85,"image":86,"author":91,"headline":65,"publisher":94,"fileFormat":97,"inLanguage":63,"description":67,"dateModified":98,"datePublished":99,"encodingFormat":97,"isAccessibleForFree":100,"interactionStatistic":101},"DigitalDocument",{"url":87,"@type":88,"width":89,"height":90},"https://docshare.wps.com/thumbnails/predicting-party-switching-through-machine-learning-and-open-data/290440.png","ImageObject",300,407,{"name":92,"@type":93},"Ivy","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-10-24","2026-09-17",true,{"@type":102,"interactionType":103,"userInteractionCount":105},"InteractionCounter",{"@type":104},"ViewAction",16,{"@type":107,"mainEntity":108},"FAQPage",[109,115,119],{"name":110,"@type":111,"acceptedAnswer":112},"What does the paper aim to predict?","Question",{"text":113,"@type":114},"The paper aims to predict future party switching among legislators in the Italian Parliament.","Answer",{"name":116,"@type":111,"acceptedAnswer":117},"How accurate is the proposed prediction method?",{"text":118,"@type":114},"The algorithm predicts party switchers with over 70% accuracy up to two months in advance.",{"name":120,"@type":111,"acceptedAnswer":121},"Which voting behaviors indicate a likely switch?",{"text":122,"@type":114},"Party switchers tend to participate more frequently in secret ballots and show a progressive decrease in coherence with their party’s majority votes before switching.","https://schema.org",{"og:url":83,"og:type":125,"og:title":65,"og:site_name":95,"og:description":67},"article",{"robots":127,"canonical":83},"index,follow",{"doc_id":129,"site_id":62},290440,1789641689,{"code":4,"msg":5,"data":132},{"doc_id":129,"user_id":133,"nickname":92,"user_avatar":134,"doc_module":4,"category_id":39,"category_name":40,"doc_title":65,"doc_description":67,"doc_content":135,"file_id":136,"file_url":137,"file_type":138,"file_size":139,"view_count":105,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":56,"language":140,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":141,"faqs":142,"seo_title":143,"seo_description":67,"update_tm":130,"read_time":144,"preview_page_count":4},549758252649,"https://ap-avatar.wpscdn.com/avatar/8000253669c5317157?_k=1778319167496531819","iScience  \nll  \nOPEN ACCESS  \nArticle  \nPredicting party switching through machine learning and open data  \nNicolo` Meneghetti, Fabio Pacini, Francesca Biondi Dal Monte, Marina Cracchiolo, Emanuele Rossi, Alberto Mazzoni, Silvestro Micera  \nsilvestro.micera@epfl.ch  \nHighlights  \nParty switching is common in Italian Parliament, involving almost 1/3 of Deputies  \nA machine learning classifier accurately predicts party switchers from voting data  \nParty switchers tend to engage more frequently in secret ballots  \nDeclining agreement with their party’s majority predicts future switchers  \nMeneghetti et al., iScience 26 , 107098  \nJuly 21, 2023 ª 2023 The Author(s) .  \n[https://doi.org/10.1016/](https://doi.org/10.1016/)[ ](https://doi.org/10.1016/)[j.isci.2023.107098](j.isci.2023.107098)  \niScience  \nll  \nOPEN ACCESS  \nArticle  \nPredicting party switching through machine learning and open data  \nNicolo` Meneghetti, 1,2 Fabio Pacini,3,4 Francesca Biondi Dal Monte,3 Marina Cracchiolo,1,2 Emanuele Rossi,3,5 Alberto Mazzoni,1,2,7 and Silvestro Micera1,2,5,6,7,8,*  \nSUMMARY  \nParliament dynamics might seem erratic at times. Predicting future voting patterns could support policy design based on the simulation of voting scenarios. The availability of open data on legislative activities and machine learning tools might enable such prediction. In our paper, we provide evidence for this statement by developing an algorithm able to predict party switching in the Italian Parliament with over 70% accuracy up to two months in advance. The analysis was based on voting data from the XVII (2013–2018) and XVIII (2018–2022) Italian legislature. We found party switchers exhibited higher participation in secret ballots and showed a progressive decrease in coherence with their party’s majority votes up to two months before the actual switch. These results show how machine learning combined with political open data can support predicting and understanding political dynamics.  \nINTRODUCTION  \nParty switching refers to changes in party affiliation among elected legislators. This behavior is present in several democracies such as Denmark, the United States, Australia, Brazil, Ecuador, the European Parliament, France, Japan, Poland, and Italy.1–3 Party switching is increasingly frequent in Italy,1 ,4 and the Italian XVII legislature (from March 5th 2013 to March 22nd 2018) has indeed set the record for the number of members of parliaments (MPs) who switched their political affiliation: in Italy’s lower house, the Chamber of Deputies, almost one out of three legislators changed their parliamentary group affiliation while serving their office.  \nScholars have reported the detrimental effect of political party switching on parties’ stability and, as a direct consequence, on democratic sustainability.5 Floor crossings can indeed dramatically change the power balance within the Parliament. This can in turn result in the distortion of electoral results or weakened opposition parties, leading to excessive power concentration.6 Efficiently predicting the likelihood of party switching by MPs would not only allow us to potentially know in advance if a given legislative proposal will receive expected support but it would also provide foresight on the overall stability of the political system.  \nParty switching was proposed to constitute a potential threat to public confidence in the transparency of the political system,7 as it makes it difficult for the voters to navigate with ease among party labels in the search for ideal candidates. Given these premises, it is easy to appreciate how party switching can constitute a risky endeavor from the point of view of politicians. Voters do not appreciate it, as they were reported to penalize legislators who switch their parties.2 , 8 ,9 As such, it is both legitimate and intriguing to inquire about the underlying human reasons of individual legislators driving the phenomenon of party switching.  \nPrevious studies have explored various","cbCaimoHFFhilTwg","https://ap.wps.com/l/cbCaimoHFFhilTwg","pdf",6800102,"English","# Highlights\n# Summary\n# Introduction\n## Background and impact of party switching\n## Prior research on determinants\n## Focus and approach of the paper","[{\"question\":\"What does the paper aim to predict?\",\"answer\":\"The paper aims to predict future party switching among legislators in the Italian Parliament.\"},{\"question\":\"How accurate is the proposed prediction method?\",\"answer\":\"The algorithm predicts party switchers with over 70% accuracy up to two months in advance.\"},{\"question\":\"Which voting behaviors indicate a likely switch?\",\"answer\":\"Party switchers tend to participate more frequently in secret ballots and show a progressive decrease in coherence with their party’s majority votes before switching.\"}]","Predicting party switching through machine learning and open data | PDF",48]