Social Media Fingerprints of Unemployment

Anexo: Supporting Information. This file contains Figures A-I, Tables A-F and Sections A-I.Recent widespread adoption of electronic and pervasive technologies has enabled the study of human behavior at an unprecedented level, uncovering universal patterns underlying human activity, mobility, and interpersonal communication. In the present work, we investigate whether deviations from these universal patterns may reveal information about the socio-economical status of geographical regions. We quantify the extent to which deviations in diurnal rhythm, mobility patterns, and communication styles across regions relate to their unemployment incidence. For this we examine a country-scale publicly articulated social media dataset, where we quantify individual behavioral features from over 19 million geo-located messages distributed among more than 340 different Spanish economic regions, inferred by computing communities of cohesive mobility fluxes. We find that regions exhibiting more diverse mobility fluxes, earlier diurnal rhythms, and more correct grammatical styles display lower unemployment rates. As a result, we provide a simple model able to produce accurate, easily interpretable reconstruction of regional unemployment incidence from their social-media digital fingerprints alone. Our results show that cost-effective economical indicators can be built based on publicly-available social media datasets.Partial funding came from the Spanish Ministry of Economy and Competitiveness through grant FIS2013-47532-C3-3-P, the Australian Government, and the Australian Research Council. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript

China Employment Law Update - February 2017

In This Issue: China Makes Two Major Moves in Its Social Insurance System Government Announces Policy to Fingerprint Foreigners Entering China Government Signals Intent to Change Laws to Improve Workplace Safety Government Working on Various Measures to Further Develop Data Privacy Protections Guangdong, Tianjin and Jiangsu enhance protections for female employees Zhejiang Province high court provides guidance on numerous labor dispute issues Former Employee Ordered to Publicly Apologize and Pay Legal Costs for Defaming Employer Shanghai Court Upholds Termination of Senior Executive with Large Personal Debt Chongqing Court Holds Two Employees Partly Liable for Their Employer\u27s Losses from Sca

Mobile Communication Signatures of Unemployment

The mapping of populations socio-economic well-being is highly constrained by the logistics of censuses and surveys. Consequently, spatially detailed changes across scales of days, weeks, or months, or even year to year, are difficult to assess; thus the speed of which policies can be designed and evaluated is limited. However, recent studies have shown the value of mobile phone data as an enabling methodology for demographic modeling and measurement. In this work, we investigate whether indicators extracted from mobile phone usage can reveal information about the socio-economical status of microregions such as districts (i.e., average spatial resolution < 2.7km). For this we examine anonymized mobile phone metadata combined with beneficiaries records from unemployment benefit program. We find that aggregated activity, social, and mobility patterns strongly correlate with unemployment. Furthermore, we construct a simple model to produce accurate reconstruction of district level unemployment from their mobile communication patterns alone. Our results suggest that reliable and cost-effective economical indicators could be built based on passively collected and anonymized mobile phone data. With similar data being collected every day by telecommunication services across the world, survey-based methods of measuring community socioeconomic status could potentially be augmented or replaced by such passive sensing methods in the future

Tweet-tales: moods of socio-economic crisis?

The widespread adoption of highly interactive social media like Twitter, Facebook and other platforms allow users to communicate moods and opinions to their social network. Those platforms represent an unprecedented source of information about human habits and socio-economic interactions. Several new studies have started to exploit the potential of these big data as fingerprints of economic and social interactions. The present analysis aims at exploring the informative power of indicators derived from social media activity, with the aim to trace some preliminary guidelines to investigate the eventual correspondence between social media indices and available labour market indicators at a territorial level. The study is based on a large dataset of about 4 million Italian-language tweets collected from October 2014 to December 2015, filtered by a set of specific keywords related to the labour market. With techniques from machine learning and user’s geolocalization, we were able to subset the tweets on specific topics in all Italian provinces. The corpus of tweets is then analyzed with linguistic tools and hierarchical clustering analysis. A comparison with traditional economic indicators suggests a strong need for further cleaning procedures, which are then developed in detail. As data from social networks are easy to obtain, this represents a very first attempt to evaluate their informative power in the Italian context, which is of potentially high importance in economic and social research

Scaling in Words on Twitter

Scaling properties of language are a useful tool for understanding generative processes in texts. We investigate the scaling relations in citywise Twitter corpora coming from the Metropolitan and Micropolitan Statistical Areas of the United States. We observe a slightly superlinear urban scaling with the city population for the total volume of the tweets and words created in a city. We then find that a certain core vocabulary follows the scaling relationship of that of the bulk text, but most words are sensitive to city size, exhibiting a super- or a sublinear urban scaling. For both regimes we can offer a plausible explanation based on the meaning of the words. We also show that the parameters for Zipf's law and Heaps law differ on Twitter from that of other texts, and that the exponent of Zipf's law changes with city size

Biometric Boom: How the Private Sector Commodifies Human Characteristics

Biometric technology has become an increasingly common part of daily life. Although biometrics have been used for decades, recent ad- vances and new uses have made the technology more prevalent, particu- larly in the private sector. This Note examines how widespread use of biometrics by the private sector is commodifying human characteristics. As the use of biometrics has become more extensive, it exacerbates and exposes individuals and industry to a number of risks and problems asso- ciated with biometrics. Despite public belief, biometric systems may be bypassed, hacked, or even fail. The more a characteristic is utilized, the less value it will hold for security purposes. Once compromised, a biome- tric cannot be replaced as would a password or other security device. This Note argues that there are strong justifications for a legal struc- ture that builds hurdles to slow the adoption of biometrics in the private sector. By examining the law and economics and personality theories of commodification, this Note identifies market failure and potential harm to personhood due to biometrics. The competing theories justify a reform to protect human characteristics from commodification. This Note presents a set of principles and tools based on defaults, disclosures, incen- tives, and taxation to discourage use of biometrics, buying time to streng- then the technology, educate the public, and establish legal safeguards for when the technology is compromised or fails

Roma expulsions and discrimination: the elephant in Brussels

This article will critically examine the treatment of migrant Roma in Western Europe, particularly Italy and France, in the light of the obligations under the E U Citizenship Directive 2004/38. The role of the political institutions will be considered, especially the European Commission, who have yet to take a decisive position on the Roma expulsions and on the wider issue of Roma discrimination in Europe. It is argued that the focus on non-discrimination cannot address the entrenched inequality which characterises the Roma's situation in Europe. Furthermore, that the comparative disadvantage experienced by Europe's Roma communities constitutes a major human rights crisis which has so far been side-lined by Brussels. A European strategy is urgently required which demands leadership from the Commission and the full participation of Roma representatives

No. 19: Irregular Migration to South Africa During the First Ten Years of Democracy

Irregular migration poses a considerable problem for South Africa in migration management, population planning, infrastructure development, resource management, governance, social services, economic development and security. A government can only work with what it knows, with a reasonable margin of error. By its nature, irregular migration creates many unknowns. Where entry into South Africa is clandestine or fraudulent, no proper account can be kept of the migrant’s presence, movement, identity, nationality, health status or activities. Without the ability to measure the problem, the ability to address it remains elusive. For years, figures on the number of irregular migrants present in South Africa have been bandied about and strongly contested. In a 1996 report, commissioned by the government, the Human Sciences Research Council (HSRC) estimated the number at between 2.5 and 4 million, but suggested it could be as high as 12 million. The HSRC used a sample survey method to estimate the number of irregular migrants in South Africa. Going from door to door across the country, surveyors asked how many noncitizens lived on the property. The sample figure was then extrapolated and the number of legally resident non-citizens, as determined by Statistics South Africa through the census, was subtracted. This manner of survey was repeated every six months in an attempt to track movement patterns of irregular migrants. Critics of the HSRC figures include Maxine Reitzes and Jonathan Crush, who suggest that it could be as low as 500 000. In 2002 the HSRC withdrew its estimate. Nevertheless, the Department of Home Affairs quotes figures of between 2.5 and 5 million or up to 7 million. The media, not being in a position to conduct independent research, moves freely between these numbers. As the debate raged, the Minister of Home Affairs pleaded that less attention be given to how many irregular migrants were present, and more be focused on whether it is a problem and what it is costing South Africa7. As the Draft Green Paper on International Migration8 states: “Speculative assessments have also been made of the impact of unauthorised migration on our education, health-care and social welfare systems. We have looked carefully at all available figures and must declare that we have little faith in them. It would, of course, be very helpful if officials and planners had accurate statistics, but even under the best circumstances these are difficult to collect as people have an interest in not declaring their presence.