71 research outputs found
Tracking Human Mobility using WiFi signals
We study six months of human mobility data, including WiFi and GPS traces
recorded with high temporal resolution, and find that time series of WiFi scans
contain a strong latent location signal. In fact, due to inherent stability and
low entropy of human mobility, it is possible to assign location to WiFi access
points based on a very small number of GPS samples and then use these access
points as location beacons. Using just one GPS observation per day per person
allows us to estimate the location of, and subsequently use, WiFi access points
to account for 80\% of mobility across a population. These results reveal a
great opportunity for using ubiquitous WiFi routers for high-resolution outdoor
positioning, but also significant privacy implications of such side-channel
location tracking
The Role of Gender in Social Network Organization
The digital traces we leave behind when engaging with the modern world offer
an interesting lens through which we study behavioral patterns as expression of
gender. Although gender differentiation has been observed in a number of
settings, the majority of studies focus on a single data stream in isolation.
Here we use a dataset of high resolution data collected using mobile phones, as
well as detailed questionnaires, to study gender differences in a large cohort.
We consider mobility behavior and individual personality traits among a group
of more than university students. We also investigate interactions among
them expressed via person-to-person contacts, interactions on online social
networks, and telecommunication. Thus, we are able to study the differences
between male and female behavior captured through a multitude of channels for a
single cohort. We find that while the two genders are similar in a number of
aspects, there are robust deviations that include multiple facets of social
interactions, suggesting the existence of inherent behavioral differences.
Finally, we quantify how aspects of an individual's characteristics and social
behavior reveals their gender by posing it as a classification problem. We ask:
How well can we distinguish between male and female study participants based on
behavior alone? Which behavioral features are most predictive
Temporal Fidelity in Dynamic Social Networks
It has recently become possible to record detailed social interactions in
large social systems with high resolution. As we study these datasets, human
social interactions display patterns that emerge at multiple time scales, from
minutes to months. On a fundamental level, understanding of the network
dynamics can be used to inform the process of measuring social networks. The
details of measurement are of particular importance when considering dynamic
processes where minute-to-minute details are important, because collection of
physical proximity interactions with high temporal resolution is difficult and
expensive. Here, we consider the dynamic network of proximity-interactions
between approximately 500 individuals participating in the Copenhagen Networks
Study. We show that in order to accurately model spreading processes in the
network, the dynamic processes that occur on the order of minutes are essential
and must be included in the analysis
Inferring Person-to-person Proximity Using WiFi Signals
Today's societies are enveloped in an ever-growing telecommunication
infrastructure. This infrastructure offers important opportunities for sensing
and recording a multitude of human behaviors. Human mobility patterns are a
prominent example of such a behavior which has been studied based on cell phone
towers, Bluetooth beacons, and WiFi networks as proxies for location. However,
while mobility is an important aspect of human behavior, understanding complex
social systems requires studying not only the movement of individuals, but also
their interactions. Sensing social interactions on a large scale is a technical
challenge and many commonly used approaches---including RFID badges or
Bluetooth scanning---offer only limited scalability. Here we show that it is
possible, in a scalable and robust way, to accurately infer person-to-person
physical proximity from the lists of WiFi access points measured by smartphones
carried by the two individuals. Based on a longitudinal dataset of
approximately 800 participants with ground-truth interactions collected over a
year, we show that our model performs better than the current state-of-the-art.
Our results demonstrate the value of WiFi signals in social sensing as well as
potential threats to privacy that they imply
Evidence of complex contagion of information in social media: An experiment using Twitter bots
It has recently become possible to study the dynamics of information diffusion in techno-social systems at scale, due to the emergence of online platforms, such as Twitter, with millions of users. One question that systematically recurs is whether information spreads according to simple or complex dynamics: does each exposure to a piece of information have an independent probability of a user adopting it (simple contagion), or does this probability depend instead on the number of sources of exposure, increasing above some threshold (complex contagion)? Most studies to date are observational and, therefore, unable to disentangle the effects of confounding factors such as social reinforcement, homophily, limited attention, or network community structure. Here we describe a novel controlled experiment that we performed on Twitter using 'social bots' deployed to carry out coordinated attempts at spreading information. We propose two Bayesian statistical models describing simple and complex contagion dynamics, and test the competing hypotheses. We provide experimental evidence that the complex contagion model describes the observed information diffusion behavior more accurately than simple contagion. Future applications of our results include more effective defenses against malicious propaganda campaigns on social media, improved marketing and advertisement strategies, and design of effective network intervention techniques
- …