482 research outputs found
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
On Uniqueness of Boundary Blow-up Solutions of a Class of Nonlinear Elliptic Equations
We study boundary blow-up solutions of semilinear elliptic equations
with , or with , where is a second order
elliptic operator with measurable coefficients. Several uniqueness theorems and
an existence theorem are obtained.Comment: To appear in Comm. Partial Differential Equations; 10 page
Does \u2018bigger\u2019mean \u2018better\u2019? Pitfalls and shortcuts associated with big data for social research
\u2018Big data is here to stay.\u2019 This key statement has a double value: is an assumption as well as the reason why a theoretical reflection is needed. Furthermore, Big data is something that is gaining visibility and success in social sciences even, overcoming the division between humanities and computer sciences. In this contribution some considerations on the presence and the certain persistence of Big data as a socio-technical assemblage will be outlined. Therefore, the intriguing opportunities for social research linked to such interaction between practices and technological development will be developed. However, despite a promissory rhetoric, fostered by several scholars since the birth of Big data as a labelled concept, some risks are just around the corner. The claims for the methodological power of bigger and bigger datasets, as well as increasing speed in analysis and data collection, are creating a real hype in social research. Peculiar attention is needed in order to avoid some pitfalls. These risks will be analysed for what concerns the validity of the research results \u2018obtained through Big data. After a pars distruens, this contribution will conclude with a pars construens; assuming the previous critiques, a mixed methods research design approach will be described as a general proposal with the objective of stimulating a debate on the integration of Big data in complex research projecting
Spatiotemporal correlations of handset-based service usages
We study spatiotemporal correlations and temporal diversities of
handset-based service usages by analyzing a dataset that includes detailed
information about locations and service usages of 124 users over 16 months. By
constructing the spatiotemporal trajectories of the users we detect several
meaningful places or contexts for each one of them and show how the context
affects the service usage patterns. We find that temporal patterns of service
usages are bound to the typical weekly cycles of humans, yet they show maximal
activities at different times. We first discuss their temporal correlations and
then investigate the time-ordering behavior of communication services like
calls being followed by the non-communication services like applications. We
also find that the behavioral overlap network based on the clustering of
temporal patterns is comparable to the communication network of users. Our
approach provides a useful framework for handset-based data analysis and helps
us to understand the complexities of information and communications technology
enabled human behavior.Comment: 11 pages, 15 figure
The network structure of visited locations according to geotagged social media photos
Businesses, tourism attractions, public transportation hubs and other points
of interest are not isolated but part of a collaborative system. Making such
collaborative network surface is not always an easy task. The existence of
data-rich environments can assist in the reconstruction of collaborative
networks. They shed light into how their members operate and reveal a potential
for value creation via collaborative approaches. Social media data are an
example of a means to accomplish this task. In this paper, we reconstruct a
network of tourist locations using fine-grained data from Flickr, an online
community for photo sharing. We have used a publicly available set of Flickr
data provided by Yahoo! Labs. To analyse the complex structure of tourism
systems, we have reconstructed a network of visited locations in Europe,
resulting in around 180,000 vertices and over 32 million edges. An analysis of
the resulting network properties reveals its complex structure.Comment: 8 pages, 3 figure
High resolution dynamical mapping of social interactions with active RFID
In this paper we present an experimental framework to gather data on
face-to-face social interactions between individuals, with a high spatial and
temporal resolution. We use active Radio Frequency Identification (RFID)
devices that assess contacts with one another by exchanging low-power radio
packets. When individuals wear the beacons as a badge, a persistent radio
contact between the RFID devices can be used as a proxy for a social
interaction between individuals. We present the results of a pilot study
recently performed during a conference, and a subsequent preliminary data
analysis, that provides an assessment of our method and highlights its
versatility and applicability in many areas concerned with human dynamics
Attention on Weak Ties in Social and Communication Networks
Granovetter's weak tie theory of social networks is built around two central
hypotheses. The first states that strong social ties carry the large majority
of interaction events; the second maintains that weak social ties, although
less active, are often relevant for the exchange of especially important
information (e.g., about potential new jobs in Granovetter's work). While
several empirical studies have provided support for the first hypothesis, the
second has been the object of far less scrutiny. A possible reason is that it
involves notions relative to the nature and importance of the information that
are hard to quantify and measure, especially in large scale studies. Here, we
search for empirical validation of both Granovetter's hypotheses. We find clear
empirical support for the first. We also provide empirical evidence and a
quantitative interpretation for the second. We show that attention, measured as
the fraction of interactions devoted to a particular social connection, is high
on weak ties --- possibly reflecting the postulated informational purposes of
such ties --- but also on very strong ties. Data from online social media and
mobile communication reveal network-dependent mixtures of these two effects on
the basis of a platform's typical usage. Our results establish a clear
relationships between attention, importance, and strength of social links, and
could lead to improved algorithms to prioritize social media content
The International Trade Network: weighted network analysis and modelling
Tools of the theory of critical phenomena, namely the scaling analysis and
universality, are argued to be applicable to large complex web-like network
structures. Using a detailed analysis of the real data of the International
Trade Network we argue that the scaled link weight distribution has an
approximate log-normal distribution which remains robust over a period of 53
years. Another universal feature is observed in the power-law growth of the
trade strength with gross domestic product, the exponent being similar for all
countries. Using the 'rich-club' coefficient measure of the weighted networks
it has been shown that the size of the rich-club controlling half of the
world's trade is actually shrinking. While the gravity law is known to describe
well the social interactions in the static networks of population migration,
international trade, etc, here for the first time we studied a non-conservative
dynamical model based on the gravity law which excellently reproduced many
empirical features of the ITN.Comment: 5 pages, 5 figure
An Arabic Corpus of Fake News: Collection, Analysis and Classification
International audienceOver the last years, with the explosive growth of social media, huge amounts of rumors have been rapidly spread on the internet. Indeed, the proliferation of malicious misinformation and nasty rumors in social media can have harmful effects on individuals and society. In this paper, we investigate the content of the fake news in the Arabic world through the information posted on YouTube. Our contribution is threefold. First, we introduce a novel Arab corpus for the task of fake news analysis, covering the topics most concerned by rumors. We describe the corpus and the data collection process in detail. Second, we present several exploratory analysis on the harvested data in order to retrieve some useful knowledge about the transmission of rumors for the studied topics. Third, we test the possibility of discrimination between rumor and no rumor comments using three machine learning classifiers namely, Support Vector Machine (SVM), Decision Tree (DT) and Multinomial Naïve Bayes (MNB)
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