Spatial popularity and similarity of watching videos in a large city

With the popularity of watching mobile videos, many works focus on the geographic features of user viewing behaviors, but few study them in the context of an entire metropolitan city. Different regions of a large city have different intensity of economy activities with respect to their different distances to the downtown, and how this will influence video popularity and similarity is still unclear. To quantitatively study the spatial popularity and similarity of watching videos in a large urban environment, we collect a dataset with two-month video view requests from the largest network provider in Shanghai, containing top six content providers, and study the spatial features of video access in regions of different scales. We find that 1) video popularity and similarity exist at different scales of city division; 2) the concentration of video popularity becomes higher as the region is closer to downtown; 3) when comparing the regions of same scale, the similarity of popular videos becomes lower as the region is farther away from the downtown. Finally, we correlate our findings with cache deployment, advertising and video recommendation to illustrate the implication

A study on Analysis and Utilization of Crowd-sourced Spatio-temporal Contexts from Social Media

兵庫県立大学大学院201

Cognition-Based Networks: A New Perspective on Network Optimization Using Learning and Distributed Intelligence

IEEE Access Volume 3, 2015, Article number 7217798, Pages 1512-1530 Open Access Cognition-based networks: A new perspective on network optimization using learning and distributed intelligence (Article) Zorzi, M.a , Zanella, A.a, Testolin, A.b, De Filippo De Grazia, M.b, Zorzi, M.bc a Department of Information Engineering, University of Padua, Padua, Italy b Department of General Psychology, University of Padua, Padua, Italy c IRCCS San Camillo Foundation, Venice-Lido, Italy View additional affiliations View references (107) Abstract In response to the new challenges in the design and operation of communication networks, and taking inspiration from how living beings deal with complexity and scalability, in this paper we introduce an innovative system concept called COgnition-BAsed NETworkS (COBANETS). The proposed approach develops around the systematic application of advanced machine learning techniques and, in particular, unsupervised deep learning and probabilistic generative models for system-wide learning, modeling, optimization, and data representation. Moreover, in COBANETS, we propose to combine this learning architecture with the emerging network virtualization paradigms, which make it possible to actuate automatic optimization and reconfiguration strategies at the system level, thus fully unleashing the potential of the learning approach. Compared with the past and current research efforts in this area, the technical approach outlined in this paper is deeply interdisciplinary and more comprehensive, calling for the synergic combination of expertise of computer scientists, communications and networking engineers, and cognitive scientists, with the ultimate aim of breaking new ground through a profound rethinking of how the modern understanding of cognition can be used in the management and optimization of telecommunication network

Urban Influencers: An Analysis of Urban Identity in YouTube Content of Local Social Media Influencers in a Super-Diverse City

Influencers belong to the daily media diet of many adolescents. As role models, they have the potential to play a crucial role in the identity construction of their viewers. In the age of social media, such role models may now be found more locally – in the same city – and perhaps with more diverse backgrounds. This may be particularly valuable to adolescents growing up in super-diverse cities, as they are surrounded by a multitude of groups and identities during a life phase in which they have to make sense of who they are and where they belong. Despite the heterogeneity of these identities, there is one thing all have in common: the city they live in. With the city as a common framework, local influencers may be important role models for these adolescents, particularly in negotiating their urban identity. This paper aims toward mapping the ways in which social media can play a role in the negotiation of urban identity among youngsters by investigating how YouTube influencers from a super-diverse city are related to each other online, and how their content relates to the (super-diverse) city of Rotterdam. Findings show that in their videos and on their channel pages, influencers mainly affiliate themselves with the city through having the city as the background and context of the videos, through their involvement with cultural trends (e.g., soccer, hip-hop) that link to the city, and through their affiliation with other local influencers. We argue that influencers may therefore provide their viewers with