arXiv subjects

Diego Caro

Publications and source records attributed to Diego Caro.

4 recordsLinked to original sources

arXiv2018

Using Compressed Suffix-Arrays for a Compact Representation of Temporal-Graphs

Temporal graphs represent binary relationships that change along time. They can model the dynamism of, for example, social and communication networks. Temporal graphs are defined as sets of contacts that are edges tagged with the temporal intervals when they are active. This work explores the use of the Compressed Suffix Array (CSA), a well-known compact and self-indexed data structure in the area of text indexing, to represent large temporal graphs. The new structure, called Temporal Graph CSA (TGCSA), is experimentally compared with the most competitive compact data structures in the state-of-the-art, namely, EDGELOG and CET. The experimental results show that TGCSA obtains a good space-time trade-off. It uses a reasonable space and is efficient for solving complex temporal queries. Furthermore, TGCSA has wider expressive capabilities than EDGELOG and CET, because it is able to represent temporal graphs where contacts on an edge can temporally overlap.

cs.DS↗

arXiv2018

Shopping Mall Attraction and Social Mixing at a City Scale

The social inclusion aspects of shopping malls and their effects on our understanding of urban spaces have been a controversial argument largely discussed in the literature. Shopping malls offer an open, safe and democratic version of the public space. Many of their detractors suggest that malls target their customers in subtle ways, promoting social exclusion. In this work, we analyze whether malls offer opportunities for social mixing by analyzing the patterns of shopping mall visits in a large Latin-American city: Santiago de Chile. We use a large XDR (Data Detail Records) dataset from a telecommunication company to analyze the mobility of $387,152$ cell phones around $16$ large malls in Santiago de Chile during one month. We model the influx of people to malls in terms of a gravity model of mobility, and we are able to predict the customer profile distribution of each mall, explaining it in terms of mall location, the population distribution, and mall size. Then, we analyze the concept of social attraction, expressed as people from low and middle classes being attracted by malls that target high-income customers. We include a social attraction factor in our model and find that it is negligible in the process of choosing a mall. We observe that social mixing arises only in peripheral malls located farthest from the city center, which both low and middle class people visit. Using a co-visitation model we show that people tend to choose a restricted profile of malls according to their socio-economic status and their distance from the mall. We conclude that the potential for social mixing in malls could be capitalized by designing public policies regarding transportation and mobility.

cs.SI↗

arXiv2018

Toward Finding Latent Cities with Non-Negative Matrix Factorization

In the last decade, digital footprints have been used to cluster population activity into functional areas of cities. However, a key aspect has been overlooked: we experience our cities not only by performing activities at specific destinations, but also by moving from one place to another. In this paper, we propose to analyze and cluster the city based on how people move through it. Particularly, we introduce Mobilicities, automatically generated travel patterns inferred from mobile phone network data using NMF, a matrix factorization model. We evaluate our method in a large city and we find that mobilicities reveal latent but at the same time interpretable mobility structures of the city. Our results provide evidence on how clustering and visualization of aggregated phone logs could be used in planning systems to interactively analyze city structure and population activity.

cs.SI↗

arXiv2017

The Effect of Pokémon Go on The Pulse of the City: A Natural Experiment

Pokémon Go, a location-based game that uses augmented reality techniques, received unprecedented media coverage due to claims that it allowed for greater access to public spaces, increasing the number of people out on the streets, and generally improving health, social, and security indices. However, the true impact of Pokémon Go on people's mobility patterns in a city is still largely unknown. In this paper, we perform a natural experiment using data from mobile phone networks to evaluate the effect of Pokémon Go on the pulse of a big city: Santiago, capital of Chile. We found significant effects of the game on the floating population of Santiago compared to movement prior to the game's release in August 2016: in the following week, up to 13.8\% more people spent time outside at certain times of the day, even if they do not seem to go out of their usual way. These effects were found by performing regressions using count models over the states of the cellphone network during each day under study. The models used controlled for land use, daily patterns, and points of interest in the city. Our results indicate that, on business days, there are more people on the street at commuting times, meaning that people did not change their daily routines but slightly adapted them to play the game. Conversely, on Saturday and Sunday night, people indeed went out to play, but favored places close to where they live. Even if the statistical effects of the game do not reflect the massive change in mobility behavior portrayed by the media, at least in terms of expanse, they do show how "the street" may become a new place of leisure. This change should have an impact on long-term infrastructure investment by city officials, and on the drafting of public policies aimed at stimulating pedestrian traffic.

cs.SI↗