Socia fingerprints of unemployment
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<strong>The following datasets are associated to the paper the "Social Fingerprints of Unemployment"</strong> Llorente A, Garcia-Herranz M, Cebrian M, Moro E (2015) Social Media Fingerprints of<br>Unemployment. PLoS ONE 10(5): e0128692. doi: 10.1371/journal.pone.0128692 http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0128692 <strong><br></strong> <strong>Description of the files in this folder</strong> This folder contains two (2) files<br><em>Tij.csv</em><br><em>table_municipalities.csv</em> <strong>Tij.csv</strong><br>This files contains the matrix Tij, i.e. the total number of trips between different municipalities in our database. The file has four columns<br>i -> the municipality origin id of the trips<br>j -> the municipality destination id of the trips<br>Tij -> the number of trips between i and j (symmetric)<br>dij -> the distance between municipalities <strong>table_municipalities.csv</strong><br>This files contains the demographic, unemployment and Twitter variables for each of the municipalities considered. The file has 16 columns<br>id -> the official id of the municipality<br>pobTOT -> total population of the municipality (as of Jan 2013)<br>pobACT -> total active (employable) population of the municipality<br>pobUNEMP -> total population unemployed in the municipality<br>pobACTYOUNG -> total active young (below 25 years) population of the municipality<br>pobUNEMPYOUNG -> total young (below 25 years) population unemployed in the municipality<br>ntwsTOT -> total number of tweets geolocalized in the municipality<br>ntwsWDAY -> total number of tweets from Monday to Friday (working days) in the municipality<br>S-geo -> Geographical Entropy of the trips from/to the municipality<br>S-social -> Social Entropy of the communications fromt/to the municipality<br>nusers -> Total number of users with "home" in the municipality (see paper text)<br>morning -> Total number of tweets between 8-10am during working days in the municipality<br>afternoon -> Total number of tweets between 3-5pm during working days in the municipality<br>night -> Total number of tweets between 12-3am during working days in the municipality<br>nmiss -> Total number of misspellers in the municipality<br>emp -> Total number of tweets mentioning "employment" Id's of the municipalities correspond with the official id's at<br>http://www.ine.es/daco/daco42/codmun/codmun10/10codmunmapa.htm
本数据集与论文《失业的社会指纹》（Social Fingerprints of Unemployment）相关。作者为Llorente A、Garcia-Herranz M、Cebrian M、Moro E，该研究于2015年发表于《公共科学图书馆·综合》（PLoS ONE）10卷5期，文章编号e0128692，数字对象标识符（DOI）：10.1371/journal.pone.0128692，原文链接：http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0128692。 本文件夹内文件说明：本文件夹包含2个文件：Tij.csv、table_municipalities.csv。 #### Tij.csv 该文件存储矩阵Tij，即本研究数据库中不同市镇间的出行总次数。文件包含4列： - i：出行的出发市镇ID - j：出行的抵达市镇ID - Tij：i与j之间的出行总次数（矩阵为对称矩阵） - dij：两市镇间的空间距离 #### table_municipalities.csv 该文件存储所有纳入研究的市镇的人口、失业及推特（Twitter）相关变量，文件共包含16列： - id：市镇官方ID - pobTOT：该市镇2013年1月总人口数 - pobACT：该市镇总劳动年龄（可就业）人口数 - pobUNEMP：该市镇失业总人口数 - pobACTYOUNG：该市镇25岁以下年轻劳动年龄人口数 - pobUNEMPYOUNG：该市镇25岁以下失业年轻人口数 - ntwsTOT：该市镇内所有已地理定位的推文总数 - ntwsWDAY：该市镇工作日（周一至周五）推文总数 - S-geo：该市镇往返出行的地理熵 - S-social：该市镇通信往来的社会熵 - nusers：以该市镇为"归属地"的用户总数（详见论文正文） - morning：该市镇工作日早8时至10时的推文总数 - afternoon：该市镇工作日下午3时至5时的推文总数 - night：该市镇工作日凌晨0时至3时的推文总数 - nmiss：该市镇内拼写错误推文总数 - emp：该市镇内提及"employment（就业）"关键词的推文总数 市镇ID与西班牙国家统计局（INE）官方ID一一对应，详见链接：http://www.ine.es/daco/daco42/codmun/codmun10/10codmunmapa.htm
