Scaling of city attractiveness for foreign visitors through big data of human economical and social media activity

Scientific studies investigating laws and regularities of human behavior are nowadays increasingly relying on the wealth of widely available digital information produced by human social activity. In this paper we leverage big data created by three different aspects of human activity (i.e., bank card transactions, geotagged photographs and tweets) in Spain for quantifying city attractiveness for the foreign visitors. An important finding of this papers is a strong superlinear scaling of city attractiveness with its population size. The observed scaling exponent stays nearly the same for different ways of defining cities and for different data sources, emphasizing the robustness of our finding. Temporal variation of the scaling exponent is also considered in order to reveal seasonal patterns in the attractivenessComment: 8 pages, 3 figures, 1 tabl

О концепции создания системы агрегации и обработки данных пользователей социальных cетей

The development of a general concept and implementation of a data-storage and analysis system for practice oriented data, one of the subsystems of which is an analytical system for the accumulation and analysis of data from users of social networks, is topical. The development of a general concept and implementation of a data-storage and analysis system for practice oriented data, one of the subsystems of which is an analytical system for the accumulation and analysis of data from users of social networks, is topical. Data that users leave about themselves in social networks can be useful in solving various tasks. The proposed article describes the subject area associated with the collection and storage of data from users of social networks. Proceeding from the subject area, the general architecture of the universal data collection and storage system is proposed, which is based on the client-server architecture. For the server side of the system, a fragment of the data model is provided, which is associated with the accumulation of data from external sources. The framework of the system architecture is described. The developed universal system is based on the information technology of data warehousing, and it has the following aspects: an expandable complex subject area, the integration of stored data that come from various sources, the invariance of stored data in time with mandatory labels, relatively high data stability, the search for necessary trade-off in data redundancy, modularity of individual system units, fl and extensibility of the architecture, high security requirements vulnerable data.The proposed system organizes the process of collecting data and filling the database from external sources. To do this, the system has a module for collecting and converting information from third-party Internet sources and sending them to the database. The system is intended for various users interested in analyzing data of users of social networks.Актуальным представляется разработка общей концепции и реализация системы хранения и анализа данных практико-ориентированной направленности, одной из подсистем которой является аналитическая система накопления и анализа данных пользователей социальных сетей. Данные, которые пользователи оставляют о себе в социальных сетях, могут быть полезны при решении различных задач. В предлагаемой статье описывается предметная область, связанная со сбором и хранением данных пользователей социальных сетей. Исходя из предметной области, предлагается общая архитектура универсальной системы сбора и хранения данных, которая базируется на клиент-серверной архитектуре. Для серверной части системы приводится фрагмент модели данных, которая связана с накоплением данных из внешних источников. Описывается каркас архитектуры системы. Разрабатываемая универсальная система базируется на информационной технологии складирования данных и для нее характерны следующие аспекты: расширяемая комплексная предметная область, интегрированность хранимых данных, которые поступают из различных источников, инвариантность хранимых данных во времени с обязательными метками, относительно высокая стабильность данных, поиск необходимых компромиссов в избыточности данных, модульность отдельных блоков системы, гибкость и расширяемость архитектуры, высокие требования к безопасности хранимых данных.Предлагаемая система организовывает процесс сбора данных и заполнения базы из сторонних источников. Для этого в системе разработан модуль для сбора и преобразования информации из Интернет-источников и отправки их в базу данных. Система предназначена для различных пользователей, заинтересованных в анализе данных пользователей социальных сетей.

Structure of 311 service requests as a signature of urban location

© 2017 Wang et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. While urban systems demonstrate high spatial heterogeneity, many urban planning, economic and political decisions heavily rely on a deep understanding of local neighborhood contexts. We show that the structure of 311 Service Requests enables one possible way of building a unique signature of the local urban context, thus being able to serve as a low-cost decision support tool for urban stakeholders. Considering examples of New York City, Boston and Chicago, we demonstrate how 311 Service Requests recorded and categorized by type in each neighborhood can be utilized to generate a meaningful classification of locations across the city, based on distinctive socioeconomic profiles. Moreover, the 311-based classification of urban neighborhoods can present sufficient information to model various socioeconomic features. Finally, we show that these characteristics are capable of predicting future trends in comparative local real estate prices. We demonstrate 311 Service Requests data can be used to monitor and predict socioeconomic performance of urban neighborhoods, allowing urban stakeholders to quantify the impacts of their interventions