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50 results for “Voting”
Replication files for: Strongmen Cry Too: The Effect of Aerial Bombing on Voting for The Incumbent in Competitive Autocracies
<p>The NATO bombing of Yugoslavia, which lasted from March 24, 1999 until June 10, 1999, was the largest air campaign in Europe since the bombing of Britain and Germany in World War II. The air raids lasted for 78 days and hit 108 out of 160 municipalities, excluding Kosovo and Montenegro. The bombing was spread out and largely aimed at military barracks, industrial facilities, transportation networks, and communication lines. This repo provides a novel dataset with information on over 1,000 targets in the Federal Republic of Yugoslavia, including the date, location, target type, and fatalities. Included is also R code for the replication of my article "Strongmen Cry Too: The Effect of Aerial Bombing on Voting for The Incumbent in Competitive Autocracies" that was accepted for publication at Journal of Peace Research.</p>
Convex inference for community discovery in signed networks (European Parliament Voting Dataset)
<p>This repository contains the necessary tools to reproduce the experiments of the paper</p> <ul> <li>G. Santatmaría, V. Gómez (2015)<br> Convex inference for community discovery in signed networks.<br> NIPS 2015 Workshop: Networks in the Social and Information Sciences</li> </ul> <p>The method first maps the MAP problem on the Potts model as a hinge-loss minimization problem (see the paper for details). To run the code you need to install psl (included here) and if you want to additionally compare with other inference methods, such as max prod belief propagation or junction tree, you need to install the libDAI library (also included here)</p> <p>The directory europeanCongressData/ (~500 Mb) contains the votings of the EU parlament, including 300 votings events from the actual term, from May 2014 to June 2015, obtained from http://www.votewatch.eu/</p> <ul> <li>data/ : json files with the european votes</li> <li>network.net : signed network built from the votes</li> <li>political_parties.txt : "ground truth" party</li> <li>community_results/ : results for different number of communities and initial vertices</li> <li>dataComputations.py : used to build the signed network</li> <li>dataProcessing.py : used to build the signed network</li> </ul> <p>We would appreciate if you cite the paper after using the data or the code.</p> <p>DEPENDENCIES</p> <p>The code has been tested in Linux Mint 18.1 Serena and Ubuntu 14.04</p> <p>- For PSL library, you need to have<br> java 1.8<br> you may need to export JAVAHOME='/usr/lib/jvm/YOURJAVA1.8FOLDER'<br> maven 3.x</p> <p>- For libDAI you will need:<br> make doxygen graphviz libboost-dev libboost-graph-dev libboost-program-options-dev libboost-test-dev libgmp-dev cimg-dev libgmp-dev</p> <p>CODE TO RUN THE FOLLOWING EXPERIMENTS:</p> <p>Compare the performance in terms of structural balance of max prod bp and our method against an exact inference method (junction tree), with different number of communities</p> <p>INSTALL</p> <p>To install the experiments you have to follow the next steps:</p> <p>1 Build the libdai library by doing: make -B on the folder (libdai)</p> <p>2 Generate the class path of the groovy project:<br> mvn clean install<br> mvn dependency:build-classpath-Dmdep.outputFile=classpath.out</p> <p>on the psl root folder (You need to have java 1.8 and maven 3.x installed)</p> <p>3 Grant exec permissions to the run.sh script</p> <p>Options</p> <p>The main python file to run the experiments is</p> <p>evaluatebalanceon_sn.py.</p> <p>It accepts the following parameters:</p> <p>1 (Int) Nodes of the graph. In order to run the junction tree we recommend to set this paremeter to 150 or less<br> 2 (Int) The number of underlying communities<br> 3 (Float) The maximum amount of unbalance for the experiments. We recommend 0.45<br> 4 (Bool) Whether to use an heuristic to find the initial node for each community or to use directly random nodes from the ground truth communities. This heuristic looks alternatively for the nodes with highest negative degree and highest positive degree. For the case when the number of communities is equal to 2 (Ising Model), the heuristic is used by default.</p> <p>An example of execution would be:</p> <p>python evaluate_balance_on_sn.py 120 3 0.45 True True</p> <p>The results of the experiments are save in the folder results/<br> Scripts</p> <p>The main script of the hinge-loss method can be found in the folder psl/psl-example/src/main/java/edu/umd/cs/example/PottsCommunities.groovy</p> <p>Authors:</p> <p>Guillermo Santamaria & Vicenc Gomez<br> Mar 5, 2017</p> <p>For further questions, please contact vicen.gomez@upf.edu</p>
Questionnaire survey among members of the Czech Pirate Party regarding the use of the online voting system Helios
<p>LimeSurvey application, where only Pirate Party members had access to the survey via a unique URL sent in an e-mail invitation that allowed members to fill out the questionnaire once. The poll ran from 22 February to 14 March 2024. 213 members out of a total of 1,179 party members completed the 19-question poll in full, a response rate of 18.6%. 16 research questions were Yes or No answers, 3 questions were socio-demographic questions focusing on gender, age and educational attainment. 47 women, 146 men and 20 respondents did not classify themselves as male or female. The age group 18-30 years included 27 respondents, 31-40 years included 93 respondents, 41-50 years included 56 respondents, 51-60 years included 24 respondents, 61-70 years included 11 respondents, 71 years and above included 2 respondents. In terms of highest completed education of the respondents, 60 have high school degree, 27 have bachelor's degree, 97 have master's degree, 13 have doctoral degree and 16 have other degree.</p>
Replication material for 'The impact of local identities on voting behaviour: A Scouse case study'
<p>This holds the replication material for the paper 'The impact of local identities on voting behaviour: A Scouse case study'</p>
Waterloo, Ontario Federal and Provincial Voting Intention and Vaccine Hesitancy
<p>This it the initial release of federal and provincial voting intention in Waterloo Region in the spring of 2022, commissioned by the Laurier Institute for the Study of Public Opinion and Policy.</p>
Multiple Partitioning of Multiplex Signed Networks: Application to European Parliament Votes
<p><strong>Presentation. </strong>For more than a decade, graphs have been used to model the voting behavior taking place in parliaments. However, the methods described in the literature suffer from several limitations. The two main ones are that 1) they rely on some temporal integration of the raw data, which causes some information loss; and/or 2) they identify groups of antagonistic voters, but not the context associated with their occurrence. In this article, we propose a novel method taking advantage of multiplex signed graphs to solve both these issues. It consists in first partitioning separately each layer, before grouping these partitions by similarity. We show the interest of our approach by applying it to a European Parliament dataset. Particularly, we study the voting behavior of French and Italian MEPs on "Agriculture and Rural Development" (AGRI) during the 2012-13 legislative year.</p> <p>These are the data used in the following paper:</p> <ul> <li>N. Arınık, R. Figueiredo, and V. Labatut, “Multiple partitioning of multiplex signed networks: Application to European Parliament votes,” <em>Social Networks</em>, vol. 60, pp. 83–102, 2020. DOI: <a href="http://doi.org/10.1016/j.socnet.2019.02.001">10.1016/j.socnet.2019.02.001</a> ⟨<a href="https://hal.archives-ouvertes.fr/hal-02082574">hal-02082574</a>⟩</li> </ul> <p><strong>Source code.</strong> The code source is accessible on GitHub: <a href="https://github.com/CompNet/MultiNetVotes">https://github.com/CompNet/MultiNetVotes</a></p> <p><strong>Citation. </strong>If you use these data our this source code, please cite the above paper.</p> <p><br><code>@Article{Arinik2020,</code><br><code> author = {Arınık, Nejat and Figueiredo, Rosa and Labatut, Vincent},</code><br><code> title = {Multiple Partitioning of Multiplex Signed Networks: Application to {E}uropean {P}arliament Votes},</code><br><code> journal = {Social Networks},</code><br><code> year = {2020},</code><br><code> volume = {60},</code><br><code> pages = {83-102},</code><br><code> doi = {10.1016/j.socnet.2019.02.001},</code><br><code>}</code><br><br>----------------------------------------------<br><strong>Details.</strong><br><br><strong># RAW INPUT FILES</strong><br>The 'itsyourparliament' folder contains all raw input files for further data processing. This is the same raw data that can be found in our previous Figshare repository: https://doi.org/10.6084/m9.figshare.5785833<br>The folder structure is as follows:<br>* itsyourparliament/<br>** domains: There are 28 domain files. Each file corresponds to a domain (such as Agriculture, Economy, etc.) and contains corresponding vote identifiers and their "itsyourparliament.eu" links.<br>** meps: There are 870 Members of Parliament (MEP) files. Each file contains the MEP information (such as name, country, address, etc.)<br>** votes: There are 7513 vote files. Each file contains the votes expressed by MEPs<br><br><strong># ROLLCALL NETWORKS</strong><br>This folder contains two separate zip files regarding rollcall networks:<br>- rollcall-networks: This folder contains only the rollcall networks that are used in the article.<br>- all-rollcall-networks: For those who are interested in other countries or domains, we make available all rollcall networks that we can extract from raw data.<br>Note that these rollcall networks constitute the layers of the input signed multplex network, as illustrated in Figure 1 of the article. Note also that we consider three vote types in our network extraction process: FOR, AGAINST and ABSTAIN.<br><br><strong># ROLLCALL PARTITIONS</strong><br>Note that MEPs who voted similarly are connected together by positive links, and are connected by negative links to MEPs that voted differently from them. MEPs who did not vote at all (ABSENT) are isolates (nodes without any<br>neighbor). We identify the factions of similarly voting MEPs in the graph by solving the Correlation Clustering problem (CC).<br>The rollcall partitions correspond to voting patterns, as illustrated in Figure 1 of the article.<br><br><strong># ROLLCALL CLUSTERING</strong><br>This folder contains the results of Steps 3 and 4 of our workflow (see Figure 1 in the article). The structure of this folder is as follows:<br>|__ votetypes=FAA/: 'FAA' means we consider three vote types in our analysis: FOR, AGAINST and ABSTAIN.<br>|__ F.purity-k=2-sil=SILHOUETTE_SCORE<br>|__ clu=CLUSTER_NO/<br>|__ network: It corresponds to the network created through the similarity network-based approach, as explained in Section 4.4 of the article.<br>|__ partition: It corresponds to the characteristic voting pattern, as explained in Section 4.4 of the article.<br>----------------------------------------------</p> <p>Funding: this research benefited from the support of the Agorantic FR 3621, as well as the FMJH Program PGMO and from the support to this program from EDF-THALES-ORANGE-CRITEO.</p>
Homophily in Voting Behavior: Evidence from Preferential Voting
<p>This is a dataset for the paper <em>"Homophily in Voting Behavior: Evidence from Preferential Voting"</em> (co-authored by Lucie Coufalová and Michal Ševčík) that allows for the replication of all regression tables and descriptive statistics.</p> <p>There are four files in the dataset:</p> <ul> <li>"rdata.csv" is the main file with data used in regressions</li> <li>"homo_occupation.csv" is an auxiliary file with data used to calculate some descriptive statistics</li> <li>"municipalities_age.csv" is an auxiliary file with data used to calculate some descriptive statistics</li> <li>"replication_data_20220910.RData" is a file that contains all tables packed and compressed for use in R.</li> </ul> <p><strong> Tables</strong><br> rdata...main data table used in regressions<br> homo_occupation...auxiliary data table used in descriptive stats<br> municipality_ages...auxiliary data table used in descriptive stats</p> <p><strong>Variables</strong><br> <em> Outcome:</em><br> pref...number of preferential votes</p> <p><em> Variables of interest:</em><br> homo_municipality...indicator variable for a candidate running in the municipality of his/her residence<br> homo_(education/occupation/age/gender)...percentage of the population sharing the characteristic of the candidate</p> <p><em> Other variables:</em><br> KOD_OBEC...municipality ID in CISOB classification<br> total_fe...ID of candidate-election pair<br> maxPORCISLO...number of candidates on the ballot<br> cluster_ID...ID for error term clustering<br> POC_HLASU...total number of votes cast for the party in the given municipality<br> small_municipality...indicator variable for a municipality with a population below the median (defined separately <br> for each year and constituency)<br> year...election year (election ID)<br> VOLKRAJ...constituency ID<br> PORCISLO...position of the candidate on the ballot<br> VEK...age<br> agecat...age category<br> MANDAT...indicator variable for elected candidates<br> tertiary_educ...indicator variable for candidates with tertiary education<br> gender...male/female<br> ger_share...indicator variable for municipality being dominated by ethnic Germans in 1930</p> <p> </p>
A questionnaire survey of expected characteristics of i-voting systems among students and graduates of agricultural colleges
<p>In order to find out the opinions on the transparency of remote electronic voting, a questionnaire survey was conducted among students and graduates of Czech universities with agricultural specialization. We assume that these are people with higher technical literacy who may be potential users of i-voting systems in farms in the near future. For the composition of the questions, the framework from Agbesi et al. (2023) was used to investigate the dimensions of transparency for Internet voting, supplemented with a few specific questions. Agbesi et al. (2023) identify five core dimensions, namely information accessibility, clarity, monitoring and verifiability, corrective action and testing, these dimensions influence the perception of transparency which in turn influences trust in the overall system. The anonymous questionnaire survey was conducted online via the Dotaznik.czu.cz platform operated by the Czech University of Life Sciences Prague. The invitation to participate in the survey was extended primarily to Czech students and graduates of agricultural universities. The questionnaire survey was conducted from 24 October 2023 to 12 May 2024. The questionnaire was freely accessible on the platform, therefore some respondents may be outside the target population within the limitations of the research. Participants were shown all information including consent to data processing on the homepage of the survey.</p> <p>Respondents answered on a seven-point Likert scale ranging from Strongly Disagree (0) to Strongly Agree (6) to statements within the five defined dimensions. A total of 177 individuals were recorded as completing the questionnaire. A total of 108 questionnaires were completed in full. Of these, 8 more questionnaires were removed because the control question "This question is not part of the survey and just helps us to detect bots and automated scripts. To confirm that you are a human, please choose 'Strongly agree' here" was answered differently than Strongly agree. Of the 100 responses examined, 64 were male, 35 were female, and 1 respondent did not indicate their gender. 72 respondents are aged 18-30, 18 aged 31-40, 5 aged 41-50, 2 aged 51-60 and 3 aged 61-70. 72 respondents have completed secondary education, 10 have a Bachelor's degree, 12 have a Master's degree and 6 have a PhD.</p>
Transkripte von elf Video-Ansprachen der Schweizer Regierung vor Volksabstimmungen. Transcripts of Eleven TV Addresses Given by the Swiss Government before Popular Votes
<p>Der Datensatz enthält Transkripte (doc, html, pdf, txt) von elf TV-Ansprachen der Schweizer Regierung vor Volksabstimmungen. Die Ansprachen wurden nach GAT 2 transkribiert. / The dataset contains transcripts (doc, html, pdf, txt) of eleven TV addresses given by the Swiss government before popular votes. The addresses were transcribed according to GAT 2.</p> <p> </p> <p><strong>Quellenangabe der Transkripte / Reference to the Transcripts</strong></p> <p>Schröter, Juliane, Keller, Stefan, 2018. Transkripte von elf Video-Ansprachen der Schweizer Regierung vor Volksabstimmungen. Transcripts of Eleven TV Addresses Given by the Swiss Government before Popular Votes. doi: 10.5281/zenodo.1324476.</p> <p><em>Falls Sie sich nur auf eines oder einige der elf Transkripte beziehen, passen Sie die Quellenangabe bitte entsprechend an. / If you are only referring to one or some of the eleven transcripts, please adopt the reference accordingly. </em></p> <p><em>Disclaimer: Die Mitglieder des Bundesrates haben mündliche Ansprachen gehalten. </em><em>Für den Wortlaut der Transkripte sind sie nicht verantwortlich. / The members of the Federal Council have delivered oral addresses. They are not responsible for the wording of the transcripts.</em></p> <p> </p> <p><strong>Quellenangaben der Videos / References to the Videos</strong></p> <p>Bundesrat, 2017a. [TV-Ansprache zum] Bundesgesetz „Unternehmenssteuerreform III“. Produziert von SRG SSR. <a href="https://www.admin.ch/gov/de/start/dokumentation/abstimmungen/20170212/bundesgesetz-ueber-steuerliche-massnahmen-zur-staerkung-der-wett.html">https://www.admin.ch/gov/de/start/dokumentation/abstimmungen/20170212/bundesgesetz-ueber-steuerliche-massnahmen-zur-staerkung-der-wett.html</a> (Abfrage: 23.05.2018).<br> <br> Bundesrat, 2017b. [TV-Ansprache zum] Energiegesetz. Produziert von SRG SSR. <a href="https://www.admin.ch/gov/de/start/dokumentation/abstimmungen/20170521/Energiegesetz.html">https://www.admin.ch/gov/de/start/dokumentation/abstimmungen/20170521/Energiegesetz.html</a> (Abfrage: 23.05.2018).<br> <br> Bundesrat, 2016. [TV-Ansprache zur] Initiative „Für Ehe und Familie gegen die Heiratsstrafe“. Produziert von SRG SSR. <a href="https://www.srf.ch/play/tv/abstimmungen-teilw--in-gebaerdensprache/video/vorlage-heiratsstrafe-sendung-mit-gebaerdensprache?id=8e482ca4-52e3-4777-b956-529ce64f96d1">https://www.srf.ch/play/tv/abstimmungen-teilw--in-gebaerdensprache/video/vorlage-heiratsstrafe-sendung-mit-gebaerdensprache?id=8e482ca4-52e3-4777-b956-529ce64f96d1</a> (Abfrage: 23.05.2018).<br> <br> Bundesrat, 2015a. [TV-Ansprache zur] Änderung des Bundesgesetzes über Radio und Fernsehen. Produziert von SRG SSR. <a href="https://www.srf.ch/play/tv/abstimmungen/video/br-ansprache-zum-rtvg?id=dd58817b-235b-472a-96a2-a67c721e6775&station=69e8ac16-4327-4af4-b873-fd5cd6e895a7">https://www.srf.ch/play/tv/abstimmungen/video/br-ansprache-zum-rtvg?id=dd58817b-235b-472a-96a2-a67c721e6775&station=69e8ac16-4327-4af4-b873-fd5cd6e895a7</a> (Abfrage: 23.05.2018).<br> <br> Bundesrat, 2015b. [TV-Ansprache zur] Präimplantationsdiagnostik. Produziert von SRG SSR. <a href="https://www.srf.ch/play/tv/ansprachen-bundesrat-in-gebaerdensprache/video/br-ueli-maurer-zum-fortpflanzungsmedizingesetz-fmedg-geb-?id=cbbecc0d-c210-41a9-8190-4d282926c3a8&station=69e8ac16-4327-4af4-b873-fd5cd6e895a7">https://www.srf.ch/play/tv/ansprachen-bundesrat-in-gebaerdensprache/video/br-ueli-maurer-zum-fortpflanzungsmedizingesetz-fmedg-geb-?id=cbbecc0d-c210-41a9-8190-4d282926c3a8&station=69e8ac16-4327-4af4-b873-fd5cd6e895a7</a> (Abfrage: 23.05.2018).<br> <br> Bundesrat, 2014a. [TV-Ansprache zur] Beschaffung des Kampfflugzeuges Gripen. Produziert von SRG SSR. <a href="https://www.srf.ch/play/tv/abstimmungen/video/bundesrat-ueli-maurer-zur-beschaffung-des-kampfflugzeuges-gripen?id=febd8e03-d4c3-42e7-b163-37e9e0d0176c&station=69e8ac16-4327-4af4-b873-fd5cd6e895a7">https://www.srf.ch/play/tv/abstimmungen/video/bundesrat-ueli-maurer-zur-beschaffung-des-kampfflugzeuges-gripen?id=febd8e03-d4c3-42e7-b163-37e9e0d0176c&station=69e8ac16-4327-4af4-b873-fd5cd6e895a7</a> (Abfrage: 23.05.2018).<br> <br> Bundesrat, 2014b. [TV-Ansprache zur] Initiative „Für den Schutz fairer Löhne“. Produziert von SRG SSR. <a href="https://www.srf.ch/play/tv/abstimmungen-teilw--in-gebaerdensprache/video/ansprache-von-bundesrat-johann-schneider-ammann-vom-20-04-2014?id=3ea16bd4-401d-4d68-9d06-b07b83582405">https://www.srf.ch/play/tv/abstimmungen-teilw--in-gebaerdensprache/video/ansprache-von-bundesrat-johann-schneider-ammann-vom-20-04-2014?id=3ea16bd4-401d-4d68-9d06-b07b83582405</a> (Abfrage: 23.05.2018).<br> <br> Bundesrat, 2014c. [TV-Ansprache zur] Initiative „Gegen Masseneinwanderung“. Produziert von SRG SSR. <a href="https://www.youtube.com/watch?v=A91gPrFXFCs">https://www.youtube.com/watch?v=A91gPrFXFCs</a> (Abfrage: 23.05.2018).<br> <br> Bundesrat, 2014d. [TV-Ansprache zur] Initiative „Pädophile sollen nicht mehr mit Kindern arbeiten dürfen“. Produziert von SRG SSR. <a href="https://www.bk.admin.ch/bk/de/home/dokumentation/volksabstimmungen/volksabstimmung-20140518.html">https://www.bk.admin.ch/bk/de/home/dokumentation/volksabstimmungen/volksabstimmung-20140518.html</a> (Abfrage: 18.04.2018).<br> <br> Bundesrat, 2013. [TV-Ansprache zum] Bundesbeschluss über die Familienpolitik. Produziert von SRG SSR. Video bereitgestellt von SRG SSR.<br> <br> Bundesrat, 2010. [TV-Ansprache] Zur Ausschaffungsinitiative und zum Gegenentwurf des Bundesrates. Produziert von SRG SSR. Video bereitgestellt von SRG SSR.</p> <p> </p> <p><strong>Quellenangabe des Transkriptionssystems / Reference to the Conventions of Transcription</strong></p> <p>Selting, Margret, Auer, Peter, Barth-Weingarten, Dagmar et al., 2009. Gesprächsanalytisches Transkriptionssystem 2 (GAT 2). Gesprächsforschung 10, 353-402.</p>
Supporting Data: Voting on the threat of exclusion in a public goods experiment
<p>Additional material for the paper:</p> <p>Dannenberg, A., Haita-Falah, C. & Zitzelsberger, S. Voting on the threat of exclusion in a public goods experiment. Exp Econ 21, 266; 10.1007/s10683-019-09609-y (2019).</p> <p> </p>
Zurich Participatory Budgeting Digital Voting Experiment
<p>This release contains the dataset from the study Designing Digital Voting Systems for Citizens: Achieving Fairness and Legitimacy in Participatory Budgeting. The experiment, conducted in March 2023 with 180 participants from ETH Zurich and the University of Zurich, explores how different voting input formats and aggregation methods (Greedy and MES) affect citizens' perceptions of fairness and trustworthiness in Participatory Budgeting (PB).</p> <p>The dataset includes:</p> <ul> <li>Voting data across six formats (A-F).</li> <li>Participants' perceptions of fairness and voting ease.</li> <li>Responses to simulated voting outcomes.</li> </ul> <p>This research is part of a Swiss National Science Foundation (SNSF) project (NRP 77 Digital Transformation, project no. 187249). </p> <h4>Citation:</h4> <p>If you use the data, please cite the study as follows:</p> <p>Joshua C. Yang, Carina I. Hausladen, Dominik Peters, Evangelos Pournaras, Regula Hänggli Fricker, and Dirk Helbing. 2024. Designing Digital Voting Systems for Citizens: Achieving Fairness and Legitimacy in Participatory Budgeting. ACM Digital Government: Research and Practice. <a href="https://doi.org/10.1145/3665332" target="_new" rel="noopener">https://doi.org/10.1145/3665332</a></p>
Sequential Vote Results of Swiss Referenda
<p>This repo contains the data introduced in</p> <blockquote> <p>Immer, A.*, Kristof, V.*, Grossglauser, M., Thiran, P., <a href="https://infoscience.epfl.ch/record/278872"><em>Sub-Matrix Factorization for Real-Time Vote Prediction</em></a>, KDD 2020</p> </blockquote> <p>These data have been collected from <a href="https://opendata.swiss/en/dataset/echtzeitdaten-am-abstimmungstag-zu-eidgenoessischen-abstimmungsvorlagen">OpenData.Swiss</a> every two minutes on two different referendum vote days: May 19, 2019, and February 9, 2020. We use these data to make real-time predictions of the referenda outcome on <a href="http://www.predikon.ch">www.predikon.ch</a>. We publish here the raw data, as retrieved in JSON format from the API. We also provide a python script to help scraping the JSON files.</p> <p>After unzipping the datasets, you can scrape the data <em>by referendum vote day </em>by doing:</p> <pre><code class="language-python">from scraper import scrape_referenda # Scrape the data from February 2, 2020. data_dir = 'path/to/2020-02-09' data = scrape_referenda(data_dir)</code></pre> <p>The <strong>data</strong> variable will be a list of datum dictionaries of the following structure:</p> <pre><code class="language-json">{ "vote": 6290, "municipality": 1, "timestamp": "2020-02-09T15:23:10", "num_yes": 222, "num_no": 482, "num_valid": 704, "num_total": 709, "num_eligible": 1407, "yes_percent": 0.3153409090909091, "turnout": 0.503909026297086 }</code></pre> <p>The datum is as follows:</p> <ul> <li><strong>vote</strong>: vote ID as defined by OpenData.Swiss</li> <li><strong>municipality</strong>: municipality ID as defined by OpenData.Swiss</li> <li><strong>timestamp</strong>: date and time at which the JSON files has been published on OpenData.Swiss</li> <li><strong>num_yes</strong>: number of "yes" in the municipality</li> <li><strong>num_no</strong>: number of "no" in the municipality</li> <li><strong>num_valid</strong>: number of valid ballots (the ones counting for the results)</li> <li><strong>numb_total</strong>: total number of ballots (including invalid ones)</li> <li><strong>num_eligible</strong>: number of registered voters</li> <li><strong>yes_percent</strong>: percentage of "yes" (computed as `num_yes / num_valid`)</li> <li><strong>turnout</strong>: turnout to the vote (computed as `num_total / num_eligible`)</li> </ul> <p> </p> <p><strong>Don't hesitate to <a href="mailto:victor.kristof@epfl.ch?subject=Question%20about%20the%20Swiss%20referenda%20dataset">reach out to us</a> if you have any questions!</strong></p> <p> </p> <p>To cite this dataset:</p> <pre><code>@inproceedings{immer2020submatrix, author = {Immer, Alexander and Kristof, Victor and Grossglauser, Matthias and Thiran, Patrick}, title = {Sub-Matrix Factorization for Real-Time Vote Prediction}, year = {2020}, booktitle={Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery \& Data Mining}, }</code></pre> <p> </p>
Verify My Vote: Voter Experience Questionnaire Results
<p><strong>Summary</strong></p> <p> </p> <p><strong><em>Dataset Information</em></strong></p> <p> </p> <p>This dataset contains responses of voters who had verified their vote using Verify My Vote (VMV) system after participating in in Royal College of Nursing and College of Podiatrists elections in August and October 2019 respectively. The data is used in research paper “Verify My Vote: Voter Experience” by Mohammed Alsadi and Steve Schneider and published in the proceedings of E-VOTE-ID 2020.</p> <p> </p> <p><strong>Dataset Characteristics</strong></p> <p>Multivariate</p> <p><strong>Number of Instances</strong></p> <p>196</p> <p><strong>Area</strong></p> <p>E-voting</p> <p><strong>Attribute Characteristics</strong></p> <p>Categorical</p> <p><strong>Number of Attributes</strong></p> <p>17</p> <p><strong>Missing Values</strong></p> <p>Yes</p> <p> </p> <p><strong><em>Questionnaire Information</em></strong></p> <p>The questionnaire consisted of fourteen 6-point Likert scale statements about the VMV system, two categorical questions representing Gender and Age range and one open-ended question asking voters about their feedback or any further comments.</p> <p>The questionnaire statements are:</p> <ol> <li>I was pleased with the opportunity to check my vote.</li> <li>I don't see the point of checking my vote.</li> <li>It was easy to check my vote.</li> <li>If given the choice I would prefer to vote on paper rather than over the Internet.</li> <li>I wouldn't usually bother with checking my vote.</li> <li>Checking my vote gave me confidence that the election result is correct.</li> <li>All elections should offer the opportunity to vote electronically.</li> <li>It was difficult to check my vote.</li> <li>This checking system keeps my vote private.</li> <li>The vote checking system is quite complicated.</li> <li>I would check my vote next time if I could.</li> <li>With this system other people cannot tell which vote is mine.</li> <li>I think everyone should check their vote if the facility is available.</li> <li>With this system I can tell how a particular person has voted.</li> <li>Please provide any further comments you may have. For example, what do you think of the vote checking system? Do you have any suggestions for how it could be improved? How easy was it to use? Any other comments?</li> <li>What is your gender? <em>(1 = Female; 2 = Male; 3 = Other; 4 = Prefer not to say)</em></li> <li>What is your age range? <em>(1 = under 25; 2 = 25-34; 3 = 35-44; 4 = 45-54; 5 = 55-64; 6 = 65 or over; 7 = Prefer not to say)</em></li> </ol> <p> </p> <p>The agreement levels used in Likert scale are:</p> <ul> <li>1 : Strongly Agree</li> <li>2 : Agree</li> <li>3 : Weakly Agree</li> <li>4 : Weakly Disagree</li> <li>5 : Disagree</li> <li>6 : Strongly Disagree</li> </ul>
Vote Against Prohibition
Political ghost sign advocating for the passage of the Twenty-first Amendment to the Constitution (cir. 1920-30s). On the corner of Shakespeare St and S. Broadway in Fells Point, Baltimore. Created using 500 photos taken with a DJI Mavic Mini and processed in RealityCapture. Source: Objaverse 1.0 / Sketchfab
Voter Autrement 2022 - The Online Experiment ("Un Autre Vote'')
<p> In April 2022, we have run a voting experiment during the French presidential election. During this experiment, participants were asked to test several alternative voting methods to elect the French president, like scoring methods, instant-runoff voting, Borda with partial rankings, majority judgement and pairwise comparisons. The experiment was both carried out <em>in situ </em>in polling stations during the first round of the presidential election (using paper ballots), and online between April 8th (two days before the first round of the election) and May 7th (using a web application). A total of 2308 participants took part in the online experiment. This dataset contains the answers provided by the participants to the online experiment, with no other processsing than a basic transformation to a set of CSV files.</p> <p>The companion paper available on this repository describes the experimental protocol, the format of the files, and summarizes the precise conditions under which this dataset is available.</p>
Votings data from Actize Citizen and ROI Portals
<p>Votings info from https://www.roi.ru/ (count of voters for every vote and type of vote) and https://ag.mos.ru/results (count of votes, vote start and end dates). All data was scrapped at June 2018.</p>
Votes from interactive polls
<p>Questions asked to participants during the workshop</p> <ol> <li>What is your area of work?</li> <li>Where are you working?</li> <li>What is more important in using monitoring data for assessing water quality impacts from CSOs?</li> <li>What regulation is better: simple or complex?</li> <li>What are current barriers against data sharing?</li> <li>If you make your CSO data transparent [what happens?]</li> <li>Would be a regulatory push (similar to EPA) effective in the EU?</li> <li>Where do you see biggest gap in CSO management?</li> <li>What instruments would you personally prefer to improve CSO management? [not polled]</li> <li>CSO in your region/city are: [how visible?]</li> <li>When existing, data on CSO are accessible [by whom?]</li> <li>An assessment of CSO at EU scale is in your opinion: [how useful?]</li> <li>If you want to make data public, at which level should it be provided?</li> <li>How important is a common data model and format?</li> <li>What is more important in using monitoring data for assessing water quality impacts from CSOs?</li> <li>Where do you see biggest gap in CSO management?</li> <li>What are your preferred next steps? [word cloud]</li> </ol>
Voting Behaviour - Knowledge from empirical studies
<p>This file contains primary data for our study that compares voting behaviour under first-past-the-post, evaluative voting, approval voting and D21 – Janeček method on the primary dataset consisting of 31 elections in the Czech Republic and secondary dataset of 11 elections from various countries. Our analysis aims to explore how voters use multiple positive and negative votes and what effects these voting rules have on different types of candidates. We also focus on strategic voting and on the factors influencing the number of votes cast by a voter. Our data show significant disparities in use of negative votes under voting methods offering more resources than FPTP but not in the positive votes. Furthermore, there are more misaligned voters under those methods than under plurality voting, however the ratio of strategic votes is comparable. Last but not least, we find that these methods favour medium and unknown candidates instead of polarising and unpopular candidates like plurality voting.</p>
RWI-GEO-VOTE: Vote Share of the German Federal Election 2017 on grid level
<p>The dataset contains the election results of the 2017 Bundestag election on a 1 x 1 km grid level. For this purpose, shapefiles of the electoral districts were distributed across the grids according to availability or grids were assigned to the nearest polling station. If neither a shapefile nor the address of the polling station was available, the votes were distributed to the grids on a population-proportional basis at the municipality level.</p>
Voting on a Trade Agreement: Firm Networks and Attitudes Toward Openness
<p>Replication package for <span>Voting on a Trade Agreement: Firm Networks and Attitudes Toward Openness</span><span> </span></p>
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