scholarly journals Climate risks, digital media, and big data: following communication trails to investigate urban communities' resilience

2019 ◽  
Vol 19 (7) ◽  
pp. 1485-1498 ◽  
Author(s):  
Rosa Vicari ◽  
Ioulia Tchiguirinskaia ◽  
Bruno Tisserand ◽  
Daniel Schertzer
Keyword(s):  
Big Data ◽  
Digital Media ◽  
Urban Areas ◽  
Visual Observation ◽  
Digital Data ◽  
Urban Resilience ◽  
Seine River ◽  
Incidence Graph ◽  
River Flood ◽  
Key Terms

Abstract. Today, when extreme weather affects an urban area, huge numbers of digital data are spontaneously produced by the population on the Internet. These “digital trails” can provide insight into the interactions existing between climate-related risks and the social perception of these risks. According to this research “big data” exploration techniques can be exploited to monitor these interactions and their effect on urban resilience. The experiments presented in this paper show that digital research can amplify key issues covered by digital media and identify the stakeholders that can influence the debate, and therefore the community's attitudes towards an issue. Three corpora of Web communication data have been extracted: press articles covering the June 2016 Seine River flood, press articles covering the October 2015 Alpes-Maritimes flood, and tweets on the 2016 Seine River flood. The analysis of these datasets involved an iteration between manual and automated extraction of hundreds of key terms, aggregated analysis of publication incidence and key term incidence, graph representations based on measures of semantic proximity (conditional distance) between key terms, automated visualisation of clusters through Louvain modularity, visual observation of the graph, and quantitative analysis of its nodes and edges. Through this analysis we detected topics and actors that characterise each press dataset, as well as frequent co-occurrences and clusters of topics and actors. Profiling of social media users gave us insights into who could influence opinions on Twitter. Through a comparison of the three datasets, it was also possible to observe how some patterns change over time, in different urban areas and in different digital media contexts.

scholarly journals Climate risks, digital media, and big data: following communication trails to investigate urban communities' resilience

2018 ◽  
Author(s):  
Rosa Vicari ◽  
Ioulia Tchiguirinskaia ◽  
Daniel Schertzer
Keyword(s):  
Big Data ◽  
Digital Media ◽  
Urban Areas ◽  
Visual Observation ◽  
Digital Data ◽  
Urban Resilience ◽  
Seine River ◽  
Climate Risks ◽  
River Flood ◽  
Key Terms

Abstract. Nowadays, when extreme weather affects an urban area, huge amounts of digital data are spontaneously produced by the population on the Internet. These digital trails can provide an insight on the interactions existing between climate related risks and the social perception of these risks. According to this research big data exploration techniques can be exploited to monitor these interactions and their effect on urban resilience. The experiments presented in this paper show that digital research can bring out the most central issues in the digital media, identify the stakeholders that have the capacity to influence the debate and, therefore, the community attitudes towards an issue. Three corpora of Web communication data have been extracted: press news covering the June 2016 Seine River flood; press news covering the October 2015 Alpes-Maritimes flood; tweets on the 2016 Seine River flood. The analysis of these datasets involves an iteration between manual and automated extraction of hundreds of key terms, network representations based on key terms co-occurrences, automated cluster visualisation based on adjacency matrix, and profiling of social media users. Visual observation of the network coupled to quantitative analysis of its nodes and edges allow obtaining an in-depth understanding of the most prominent topics and actors, as well as of the connections and clusters that these topics and actors tend to form in the journalistic sphere. Through a comparison of the three datasets, it is also possible to observe how these patterns change over time, in different urban areas and in different digital media contexts.

Applications of Big Data and Green IoT-Enabling Technologies for Smart Cities

2019 ◽  
pp. 22-41
Author(s):  
Onur Dogan ◽  
Omer Faruk Gurcan
Keyword(s):  
Big Data ◽  
Traffic Congestion ◽  
Urban Areas ◽  
Smart Cities ◽  
Digital Data ◽  
Rapid Urbanization ◽  
Data Resource ◽  
Parallel Data ◽  
Information And Communication

In recent years, enormous amounts of digital data have been generated. In parallel, data collection, storage, and analysis technologies have developed. Recently, there has been an increasing trend of people moving towards urban areas. By 2030 more than 60% of the world's population will live in an urban environment. Urban areas are big data resource because they include millions of citizens, technological devices, and vehicles which generate data continuously. Besides, rapid urbanization brings many challenges, such as environmental pollution, traffic congestion, health problems, energy management, etc. Some policies for countries are required to cope with urbanization problems. One of these policies is to build smart cities. Smart cities integrate information and communication technology and various physical devices connected to the network (the internet of things or IoT) to both improve the quality of government services and citizen welfare. This chapter presents a literature review of big data, smart cities, IoT, green-IoT concepts, using technology and methods, and applications worldwide.

scholarly journals Digital Transformation, Big Data and Research Landscape in Digital Communication

2018 ◽  
Vol 3 (2) ◽  
Author(s):  
Imam Syafganti
Keyword(s):  
Big Data ◽  
Digital Media ◽  
Research Method ◽  
Social Research ◽  
Digital Data ◽  
Communication Research ◽  
Research Directions ◽  
Critical Issues ◽  
Data Source ◽  
Media Research

The digitization of communications technology has led to an intense interaction between human and digital-based technology. A large number of digital data traces produced by humans as a result of that activity. Such data is commonly referred to Big Data. The availability of Big Data as a digital data source in turn, opens opportunities for communication scientists to be able to use that data to get the patterns and trends of human activities that have been done through social research. It is necessary to understand the basic concept of the Big Data, using appropriate tools and adequate access to the data, and appropriate research method in order to be able to conduct research by using such digital data. This paper aims to describe the potential of Big Data for the purposes of communication research, the use of appropriate tools, techniques and methods and to identify potential research directions in the digital realm. Some limitations and critical issues related to the research validity, population and sample, as well as ethics in digital media research method were also discussed.

Applications of Big Data and Green IoT-Enabling Technologies for Smart Cities

2022 ◽  
pp. 1090-1109
Author(s):  
Onur Dogan ◽  
Omer Faruk Gurcan
Keyword(s):  
Big Data ◽  
Traffic Congestion ◽  
Urban Areas ◽  
Smart Cities ◽  
Digital Data ◽  
Rapid Urbanization ◽  
Data Resource ◽  
Parallel Data ◽  
Information And Communication

In recent years, enormous amounts of digital data have been generated. In parallel, data collection, storage, and analysis technologies have developed. Recently, there has been an increasing trend of people moving towards urban areas. By 2030 more than 60% of the world's population will live in an urban environment. Urban areas are big data resource because they include millions of citizens, technological devices, and vehicles which generate data continuously. Besides, rapid urbanization brings many challenges, such as environmental pollution, traffic congestion, health problems, energy management, etc. Some policies for countries are required to cope with urbanization problems. One of these policies is to build smart cities. Smart cities integrate information and communication technology and various physical devices connected to the network (the internet of things or IoT) to both improve the quality of government services and citizen welfare. This chapter presents a literature review of big data, smart cities, IoT, green-IoT concepts, using technology and methods, and applications worldwide.

scholarly journals Simulation of energy consumption in urban areas

2020 ◽  
Vol 152 ◽  
pp. 02006
Author(s):  
Nikolay Garyaev
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
Energy Consumption ◽  
Urban Areas ◽  
Energy Supply ◽  
Digital Data ◽  
Successful Implementation ◽  
Digital Models ◽  
Balanced Distribution ◽  
The Way

One of the problems that may arise in the way of successful implementation of energy supply in urban areas is the difficulty of analyzing and interpreting a large amount of digital data received from various sensors. This problem may adversely affect the performance of energy organizations. The purpose of this study is to study modern tools to solve the problem of processing big data using technologies of simulation and artificial intelligence. This study is dedicated to the development of innovative digital models for the balanced distribution of energy consumption in urban areas.

scholarly journals Hazards, Infrastructure Networks and Unspecific Resilience

2021 ◽  
Vol 13 (9) ◽  
pp. 4972
Author(s):  
Nabil Touili
Keyword(s):  
Case Studies ◽  
Food Supply ◽  
Terrorist Attack ◽  
Electric Energy ◽  
Critical Infrastructures ◽  
Urban Resilience ◽  
Seine River ◽  
Urban Services ◽  
River Flood ◽  
Energy Transportation

The aim of this paper is to provide a framework to improve urban resilience independently of the nature of the disturbances. Recent disasters had a significant impact on critical infrastructures providing essential urban services such as energy, transportation, telecommunication, water and food supply or health care. Indeed, several natural and human-made hazards may lead to disruptions, and most critical infrastructures are networked and highly interdependent. Henceforth, resilience building remain focused on specific hazards or on improving the resilience, separately, of single infrastructures. In order to enhance urban resilience, this paper is based on learnings from three case studies that are the 2001 WTC terrorist attack, hurricanes Irma and Maria in 2017 and the 2016 Seine river flood in Paris. These events highlight disruptions to urban services, but also some resilience options. In light of both the literature and our case studies, a framework of unspecific resilience is provided for improving some resilience principles, namely omnivory, redundancy, buffering, high flux, homeostasis and flatness within electric energy, water and food supply and transportation networks. Rebuilding resilience within this framework is further discussed with respect to all kinds of disruptive events.

scholarly journals THE DEAD SPEAK: BIG DATA AND DIGITALLY MEDIATED DEATH

2020 ◽  
Author(s):  
Justin Grandinetti ◽  
Tyler DeAtley ◽  
Jeffery Bruinsma
Keyword(s):  
Big Data ◽  
Digital Media ◽  
Streaming Media ◽  
Economic Value ◽  
Digital Data ◽  
Data Streaming ◽  
Loved One ◽  
User Data ◽  
The Dead ◽  
The Individual

In the following panel, we add to scholarly challenges regarding the binary distinction between life and death by examining new strategies of making productive the data of the dead. Digital media and tactics of big data collection, storage, and processing blur the boundaries of human lifecycles, allowing the individual to exist as a productive part of sociotechnical apparatuses long after their corporeal demise. Specifically, our presentations on digital data and death focus on the topics of subjectivation, consent and privacy, and commodification. Reanimator: Haunted Data, Streaming Media, and Subjectivity examines the process of subjectivation taking into account the haunted data and digital afterlives of streaming media. Here, the living and bounded subject is challenged by compositions of big data, platforms, infrastructures, and algorithms that offer the possibility of a productive sociotechnical economic subject unbounded from the human body. Grief by the Byte: Constructions of Data Consent, Privacy, and Stability in Griefbots interrogates the data practices and ethics related to the creation of chatbots from the data of deceased individuals. While “griefbots” are framed as helpful to those grieving a lost loved one, there remain questions about consent and privacy that accompany these interactions. Finally, What is Dead May Never Die: The Commodification of Death in Social Media studies how user data maintains economic value after death via networks designed to surveil, collect, and commodify the immaterial labor of the dead. These practices enable a possible economic future largely influenced by the data of the dead.

scholarly journals Práticas linguísticas em Big Data / Practical language in Big Data

2017 ◽  
Vol 10 (1) ◽  
pp. 31-52
Author(s):  
Vinícius Vargas Vieira dos Santos
Keyword(s):  
Big Data ◽  
Web 2.0 ◽  
Digital Media ◽  
Mass Communication ◽  
High Speed ◽  
Digital Data ◽  
Current Configuration ◽  
Time Space ◽  
Technology Services ◽  
High Speed Data

RESUMO: O presente artigo objetiva tratar possíveis relações entre novas mídias digitais e certos aspectos conceituais da linguagem, como significado e performatividade. Big data é o termo que se refere ao acúmulo de dados digitais que caracterizou as mídias de comunicação em massa nas duas últimas décadas e está diretamente relacionado à atual configuração da plataforma de serviços de tecnologia Web 2.0. As escalas de desmedido volume e variedade de dados digitais e altos índices de velocidade que caracterizam o Big data modificam as paisagens de contexto social, provocando, consequentemente, atualizações nas escalas da linguagem. Afinal, contextos em ambientes virtuais entram em colapso, pois ao assumir as próprias características do meio, revelam-se superdiversos, simultâneos, fragmentados, não estruturados, ausentes de marcadores familiares, excedendo escalas tradicionais de tempo, espaço e alcance social. ABSTRACT: This article aims at assimilating possible relationships among new digital media and certain conceptual aspects of language, such as meaning and performativity. Big data is a term that refers to digital data accumulation that characterized the mass communication media in the last two decades and it is directly related to the current configuration of Web 2.0 technology services platform. The scales of excessive quantity and variety of digital data and high speed data which characterize the Big data change the social context of landscapes, causing consequently updates on the scales of language. After all, contexts in virtual environments collapse, because they assume the characteristics of the environment, that is, they show themselves as superdiverse, simultaneous, fragmented, unstructured, missing family markers, exceeding traditional scales of time, space and social reach.

Big Data and Communication Research

2016 ◽  
Author(s):  
Ralph Schroeder
Keyword(s):  
Big Data ◽  
Digital Media ◽  
Interpersonal Communication ◽  
Political Communication ◽  
Mobile Communication ◽  
Analytical Framework ◽  
Digital Data ◽  
Communication Research ◽  
Or Groups ◽  
Filter Bubble

Communication research has recently had an influx of groundbreaking findings based on big data. Examples include not only analyses of Twitter, Wikipedia, and Facebook, but also of search engine and smartphone uses. These can be put together under the label “digital media.” This article reviews some of the main findings of this research, emphasizing how big data findings contribute to existing theories and findings in communication research, which have so far been lacking. To do this, an analytical framework will be developed concerning the sources of digital data and how they relate to the pertinent media. This framework shows how data sources support making statements about the relation between digital media and social change. It is also possible to distinguish between a number of subfields that big data studies contribute to, including political communication, social network analysis, and mobile communication. One of the major challenges is that most of this research does not fall into the two main traditions in the study of communication, mass and interpersonal communication. This is readily apparent for media like Twitter and Facebook, where messages are often distributed in groups rather than broadcast or shared between only two people. This challenge also applies, for example, to the use of search engines, where the technology can tailor results to particular users or groups (this has been labeled the “filter bubble” effect). The framework is used to locate and integrate big data findings in the landscape of communication research, and thus to provide a guide to this emerging area.

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