DOI: 10.6084/m9.figshare.5785833
title: NetVotes 2017 - iKnow’17

description: This is the data used in the experiment of the paper submited to the following conference:<br>N. Arinik, R. Figueiredo, V. Labatut, Signed graph analysis for the interpretation of voting behavior, in: International Conference on Knowledge Technologies and Data-driven Business - International Workshop on Social Network Analysis and Digital Humanities, Graz, AT, 2017.<br>URL http://ceur-ws.org/Vol-2025/paper_rssna_1.pdf<br>The code source is accessible here: https://github.com/CompNet/NetVotes<br><br><br># RAW INPUT FILES<br>The 'itsyourparliament' folder contains all raw input files for further data processing (such as network extraction).<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 870 Member 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><br># NETWORKS AND CORRESPONDING PARTITIONS<br>This work studies the voting behavior of French and Italian MEPs on "Agriculture and Rural Development" (AGRI) and "Economic and Monetary Affairs" (ECON) for each separate year of the 7th EP term (2009-10, 2010-11, 2011-12, 2012-13, 2013-14). Note that the interpretation part (section 4) of the published paper are limited to only a few instances of them (2009-10 in ECON and 2012-13 in AGRI).<br>The extracted networks are located in the "networks" folder and the corresponding partitions are in the "partitions" folder. Both folders has the same folder structure and it is as follows:<br>COUNTRY-NAME<br>|__DOMAIN-NAME<br>|__2009-10<br>|__2010-11<br>|__2011-12<br>|__2012-13<br>|__2013-14<br><br><br><br>## NETWORKS<br>The networks in this folder are used in the article. All those networks are the ones obtained after the filtering step (as explained in the article). The networks are in 'Graphml' format. These networks are enriched with some MEPs' properties (such as name, political party, etc.) associated with each node.<br><br>## ALL NETWORKS<br>For those who are interested in other countries or domains, we make available all possible networks that we can extract from raw data with vs. without filtering step.<br><br> COUNTRY-NAME<br> |__m3<br> |__negtr=NA_postr=NA: This folder contains all filtered networks. Note that the filtering step is explained in Section 2.1.2 of the article.<br> |__bygroup<br> |__bycountry<br> |__negtr=0_postr=0: This folder contains all original networks (i.e. no filtering step).<br> |__bygroup<br> |__bycountry<br><br><br>## PARTITIONS<br>The partitions are obtained in this way: First, the Ex-CC (exact) method is run and we denote 'k' for the the number of detected cluster in output. This 'k' value is the reference point in order to run the ILS-RCC (heuristic) method by specifying the number of desired cluster in output. Then, ILS-RCC is run with various values ('k', 'k+1', 'k+2'). All those results are integrated into the initial network graphml files and then converted into gephi format so that this will help dive in the results in interactive way.<br><br>Note that we need to handle the absent MEPs in clustering results. Because, those MEPs correspond to isolated nodes in networks. Each isolated node is considered a single cluster node in Ex-CC results. We simply omit those nodes in order to find the 'k' (number of detected cluster) value before running ILS-RCC. Not also that ILS-RCC does not process isolated nodes such that an isolated node can be part of a cluster.<br><br><br># COMPARISON RESULTS<br>The 'material-stats' folder contains all the comparison results obtained for Ex-CC and ILS-CC. The csv files associated with plots are also provided.<br><br>The folder structure is as follows:<br>* material-stats/<br>** execTimePerf: The plot shows the execution time of Ex-CC and ILS-CC based on randomly generated complete networks of different size.<br>** graphStructureAnalysis: The plots show the weights and links statistics for all instances.<br>** ILS-CC-vs-Ex-CC: The folder contains 4 different comparisons between Ex-CC and ILS-CC: Imbalance difference, number of detected clusters, difference of the number of detected clusters, NMI (Normalized Mutual Information)