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Estimating Latent People Flow without Tracking Individuals

Yusuke Tanaka, Tomoharu Iwata, Takeshi Kurashima, Hiroyuki Toda, Naonori Ueda
2018 Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence  
This paper proposes a probabilistic model for estimating unobserved transition populations between locations from only aggregated data.  ...  Since the location information of people is often aggregated for protecting privacy, it is not straightforward to estimate transition populations between locations from aggregated data.  ...  Our model can infer latent people flows from only aggregated data by considering the flow conservation constraints that incorporate travel duration distributions.  ... 
doi:10.24963/ijcai.2018/494 dblp:conf/ijcai/TanakaIKTU18 fatcat:q2vxh7eggbgd3jocfccnsjpfye

Large Scale Model for Information Dissemination with Device to Device Communication using Call Details Records [article]

Rachit Agarwal and Vincent Gauthier and Monique Becker and Thouraya Toukabri and Hossam Afifi
2014 arXiv   pre-print
In order to provide a realistic model for the information dissemination, we extract a spatial distribution of the population of Ivory Coast from census data and determine migration pattern from the Call  ...  Detail Records (CDR) obtained during the Data for Development (D4D) challenge.  ...  For the mobility model, we look for the steady state limit solution.  ... 
arXiv:1305.5675v5 fatcat:udzunk5f5navfcxarcxu6yxpgy

Large scale model for information dissemination with device to device communication using call details records

Rachit Agarwal, Vincent Gauthier, Monique Becker, Thouraya Toukabrigunes, Hossam Afifi
2015 Computer Communications  
For the mobility model, we look for the steady state limit solution.  ...  In order to know the flow of people between the subprefectures, we use the Call Detail Records (CDR) provided by the Orange Labs during the Data for Development (D4D) Challenge [16] .  ... 
doi:10.1016/j.comcom.2014.12.010 fatcat:cs6tmisx75crzgkch72prjy6c4

Urban Context Detection and Context-Aware Recommendation via Networks of Humans as Sensors [chapter]

Sergio Alvarez-Napagao, Arturo Tejeda-Gómez, Luis Oliva-Felipe, Dario Garcia-Gasulla, Victor Codina, Ignasi Gómez-Sebàstia, Javier Vázquez-Salceda
2015 Communications in Computer and Information Science  
situations in the city that may affect large groups of people at a certain location, e.g., public demonstrations or celebrations, sudden traffic jams caused by accidents, and 3. enable services to users  ...  In the case of this paper, we present part of the work done in the EU project SUPERHUB and introduce how geolocated positioning coming from such devices can be used to infer the current context of the  ...  For instance, thanks to smartphones, users that move in a city can potentially generate automatic data that may be hard to obtain otherwise: location, movement flow, average trip times, and so on.  ... 
doi:10.1007/978-3-662-46241-6_7 fatcat:bymmxic2rvcp7fljaztxoc7yxa

Megacities as drivers of national outbreaks: The 2017 chikungunya outbreak in Dhaka, Bangladesh

Ayesha S. Mahmud, Md. Iqbal Kabir, Kenth Engø-Monsen, Sania Tahmina, Baizid Khoorshid Riaz, Md. Akram Hossain, Fahmida Khanom, Md. Mujibor Rahman, Md. Khalilur Rahman, Mehruba Sharmin, Dewan Mashrur Hossain, Shakila Yasmin (+4 others)
2021 PLoS Neglected Tropical Diseases  
These dynamics are difficult to capture using traditional approaches, and we compare our results to a standard diffusion model, to highlight the value of real-time data from mobile phones for outbreak  ...  We combine the modeled dynamics of chikungunya in Dhaka, with mobility estimates derived from mobile phone data for over 4 million subscribers, to understand the role of population mobility on the spatial  ...  Cases from districts outside Dhaka were only reported for a short period of time, between July 17 and August 10, and thus, the start of the outbreak could not be inferred from the data to compare with  ... 
doi:10.1371/journal.pntd.0009106 pmid:33529229 pmcid:PMC7880496 fatcat:pfiv3oohifbl5btj7z5nfdq4om

Integrating social sensors and pervasive services: approaches and perspectives

Alberto Rosi, Marco Mamei, Franco Zambonelli
2013 International Journal of Pervasive Computing and Communications  
At the other extreme, it is possible exploiting a social network as an infrastructure for the integration, by having data from pervasive devices flow towards social networks.  ...  Design/methodology/approach -From the analysis of existing proposals and prototypes, the authors found out that the process of integrating social and pervasive sensing can follow a limited number of approaches  ...  Our idea is that privacy management should apply at different levels of content information, from single personal contextual information, to aggregated one, to inferred above.  ... 
doi:10.1108/ijpcc-09-2013-0022 fatcat:o3ftu6sskfap7n222arjyktegi

Data-driven Computational Social Science: A Survey

Jun Zhang, Wei Wang, Feng Xia, Yu-Ru Lin, Hanghang Tong
2020 Big Data Research  
In this paper, to the best of our knowledge, we present a survey on data-driven computational social science for the first time which primarily focuses on reviewing application domains involving human  ...  The state-of-the-art research on human dynamics is reviewed from three aspects: individuals, relationships, and collectives.  ...  Collective Behavior Prediction Collective behavior refers to behaviors of individuals in the space at the same time, but it is not just the aggregation of individual behaviors.  ... 
doi:10.1016/j.bdr.2020.100145 fatcat:jazh5b3itfgmvh4pn37l4v5m7y

Learning Periodic Human Behaviour Models from Sparse Data for Crowdsourcing Aid Delivery in Developing Countries [article]

James McInerney, Alex Rogers, Nicholas R. Jennings
2013 arXiv   pre-print
To learn such behaviour models from sparse data (i.e., cell tower observations), we develop a Bayesian model of human mobility.  ...  Using real cell tower data of the mobility behaviour of 50,000 individuals in Ivory Coast, we find that our model outperforms the state of the art approaches in mobility prediction by at least 25% (in  ...  Proof : Let pr(v|t v ) be the probability that a given participant is at location v at time t v , obtained from a mobility model (which, we emphasise, describes individual behaviour and is distinct from  ... 
arXiv:1309.6846v1 fatcat:gjs6j7oa5rbh3nfjazcegu7k5q

Analyzing the Dynamics of Communication in Online Social Networks [chapter]

Munmun De Choudhury, Hari Sundaram, Ajita John, Doree Duncan Seligmann
2010 Handbook of Social Network Technologies and Applications  
and finally discuss large-scale quantitative observational studies for each of these organizing ideas.  ...  approach to developing a comprehensive understanding of these aspects in this disseration is essentially computational as well as empirical: I present characterization techniques, develop computational models  ...  Figure 3 . 1 : 31 Schematic representation of the data model used for predicting communication flow.  ... 
doi:10.1007/978-1-4419-7142-5_4 fatcat:d2mn6rm64zg2bdgo4kdoysyi64

Mobile Networks and Internet of Things Infrastructures to Characterize Smart Human Mobility

Luís Rosa, Fábio Silva, Cesar Analide
2021 Smart Cities  
Finally, based on this discussion, we propose paths for future smart human mobility researches.  ...  Accordingly, Artificial Intelligence (AI) has been utilized as a new paradigm for the design and optimization of mobile networks with a high level of intelligence.  ...  Informed Consent Statement: Informed consent was obtained from all subjects involved in the study. Data Availability Statement: No new data were created or analyzed in this study.  ... 
doi:10.3390/smartcities4020046 fatcat:lndroanudzbe7hfm53mzy2jph4

Emerging Technologies for Smart Cities' Transportation: Geo-Information, Data Analytics and Machine Learning Approaches

Kenneth Li-Minn Ang, Jasmine Kah Phooi Seng, Ericmoore Ngharamike, Gerald K. Ijemaru
2022 ISPRS International Journal of Geo-Information  
The paper gives a comprehensive review and discussion with a focus on emerging technologies from several information and data-driven perspectives including (1) geoinformation approaches; (2) data analytics  ...  The paper contains core discussions on the impacts of geo-information on SC transportation, data-driven transportation and big data technology, machine learning approaches for SC transportation, innovative  ...  Data Availability Statement: Not applicable. Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/ijgi11020085 fatcat:bjkv6cu7zbfqbl7q7ezfhai5ya

Literature Survey on Interplay of Topics, Information Diffusion and Connections on Social Networks [article]

Kuntal Dey, Saroj Kaushik, L. Venkata Subramaniam
2017 arXiv   pre-print
Researchers have attempted to model information diffusion and topic trends and lifecycle on online social networks.  ...  The current article presents a survey of representative models that perform topic analysis, capture information diffusion, and explore the properties of social connections in the context of online social  ...  They collect data for 996 top Twitter users from Singapore in terms of number of followers, as per twitterholic.com.  ... 
arXiv:1706.00921v1 fatcat:doqorr3v2zhq5oiemm5zhlmc3u

Large-Scale Mobile Traffic Analysis: A Survey

Diala Naboulsi, Marco Fiore, Stephane Ribot, Razvan Stanica
2016 IEEE Communications Surveys and Tutorials  
This article surveys the literature on analyses of mobile traffic collected by operators within their network infrastructure.  ...  This is a recently emerged research field, and, apart from a few outliers, relevant works cover the period from 2005 to date, with a sensible densification over the last three years.  ...  Aggregated mobility flows. Results change when considering whether the aggregated movement of large flows can be reliably inferred from CDR.  ... 
doi:10.1109/comst.2015.2491361 fatcat:2an7rvsbknehbh2xekbwlpka74

Big Data for Social Sciences: Measuring patterns of human behavior through large-scale mobile phone data [article]

Pål Sundsøy
2017 arXiv   pre-print
Big Data for efficient marketing: Finally, the dissertation offers an insight into how anonymised mobile phone data can be used to map out large social networks, covering millions of people, to understand  ...  The size of the datasets analysed ranges from 500 million to 300 billion phone records, covering millions of people. The key contributions are two-fold: 1.  ...  Doing research on 'Big Data' applied to social sciences has been my main focus during these years, and the interest in this subject has increased gradually throughout my time at Telenor.  ... 
arXiv:1702.08349v1 fatcat:q73dimeqtvdkbpsjjzwed57zqu

An Information Diffusion-Based Recommendation Framework for Micro-Blogging

Jiesi Cheng, Aaron Sun, Daning Hu, Daniel Zeng
2011 Journal of the AIS  
Research Article Micro-blogging is increasingly evolving from a daily chatting tool into a critical platform for individuals and organizations to seek and share real-time news updates during emergencies  ...  By analyzing information diffusion patterns among a large set of micro-blogs that play the role of emergency news providers, our approach selects a small subset as recommended emergency news feeds for  ...  At the time we collected data for this study, we could only extract self-proclaimed location information from public user profiles. Such data can be incomplete or inaccurate.  ... 
doi:10.17705/1jais.00271 fatcat:qs6oh2lr3nftlkrlhrbezligxa
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