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

2018 ◽  
Author(s):  
Anonymous
Keyword(s):  
Big Data ◽  
Urban Communities ◽  
Digital Media ◽  
Climate Risks

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.

scholarly journals Big data actionable intelligence architecture

2020 ◽  
Vol 7 (1) ◽  
Author(s):  
Tian J. Ma ◽  
Rudy J. Garcia ◽  
Forest Danford ◽  
Laura Patrizi ◽  
Jennifer Galasso ◽  
...  
Keyword(s):  
Big Data ◽  
Real Time ◽  
Digital Media ◽  
Decision Makers ◽  
Time Data ◽  
Human In The Loop ◽  
Course Of Action ◽  
Insufficient Time ◽  
Data Source ◽  
Different Sources

AbstractThe amount of data produced by sensors, social and digital media, and Internet of Things (IoTs) are rapidly increasing each day. Decision makers often need to sift through a sea of Big Data to utilize information from a variety of sources in order to determine a course of action. This can be a very difficult and time-consuming task. For each data source encountered, the information can be redundant, conflicting, and/or incomplete. For near-real-time application, there is insufficient time for a human to interpret all the information from different sources. In this project, we have developed a near-real-time, data-agnostic, software architecture that is capable of using several disparate sources to autonomously generate Actionable Intelligence with a human in the loop. We demonstrated our solution through a traffic prediction exemplar problem.

scholarly journals Design on Big data Platform-based in Higher Education Institute

2020 ◽  
Vol 10 (4) ◽  
pp. 36
Author(s):  
Sajeewan Pratsri ◽  
Prachyanun Nilsook
Keyword(s):  
Higher Education ◽  
Big Data ◽  
Data Analysis ◽  
Digital Media ◽  
Data Storage ◽  
Security And Privacy ◽  
Digital Learning ◽  
Learning Platform ◽  
Data Platform ◽  
Tools And Techniques

According to a continuously increasing amount of information in all aspects whether the sources are retrieved from an internal or external organization, a platform should be provided for the automation of whole processes in the collection, storage, and processing of Big Data. The tool for creating Big Data is a Big Data challenge. Furthermore, the security and privacy of Big Data and Big Data analysis in organizations, government agencies, and educational institutions also have an impact on the aspect of designing a Big Data platform for higher education institute (HEi). It is a digital learning platform that is an online instruction and the use of digital media for educational reform including a module provides information on functions of various modules between computers and humans. 1) Big Data architecture is a framework for an architecture of numerous data which consisting of Big Data Infrastructure (BDI), Data Storage (Cloud-based), processing of a computer system that uses all parts of computer resources for optimal efficiency (High-Performance Computing: HPC), a network system to detect the target device network. Thereafter, according to Hadoop’s tools and techniques, when Big Data was introduced with Hadoop's tools and techniques, the benefits of the Big Data platform would provide desired data analysis by retrieving existing information, to illustrate, student information and teaching information that is large amounts of information to adopt for accurate forecasting.

Context collapse and anonymity among queer Reddit users

2019 ◽  
pp. 146144481989035 ◽  
Author(s):  
Anthony Henry Triggs ◽  
Kristian Møller ◽  
Christina Neumayer
Keyword(s):  
Social Media ◽  
Big Data ◽  
Digital Media ◽  
Queer People ◽  
Social Media Platforms ◽  
Queer Communities ◽  
Four Levels

This article maps out how people in queer communities on Reddit navigate context collapse. Drawing upon data from interviews with queer Reddit users and insights from other studies of context collapse in digital media, we argue that context collapse also occurs in anonymity-based social media. The interviews reveal queer Reddit users’ practices of context differentiation, occurring at four levels: somatic, system, inter-platform and intra-platform. We use these levels to map out how lesbian, gay, bisexual, transgender and queer or questioning (LGBTQ) people express their identities and find community on Reddit while seeking to minimize the risks imposed by multiple impending context collapses. Because living an authentic queer life can make subjects vulnerable, we find that despite Reddit’s anonymity, sophisticated practices of context differentiation are developed and maintained. We argue that context collapse in an era of big data and social media platforms operates beyond the control of any one user, which causes problems, particularly for queer people.

How Datafication Drives Legacy Newspapers to Change Their Advertising Model for Business Survival

2019 ◽  
Vol 1 (2) ◽  
pp. 62-74
Author(s):  
Luis Sangil
Keyword(s):  
Big Data ◽  
Real Time ◽  
Digital Media ◽  
Business Performance ◽  
Business Survival ◽  
Technological Advances ◽  
Key Factor ◽  
Revenue Models ◽  
Advertising Model ◽  
Digital Newspapers

Technological advances have introduced changes in digital media business and funding models. Traditional “legacy” newspapers are reacting to the superior business performance of digital intermediaries such as Google and Facebook, which capture a big part of total digital advertising revenues. This work describes the change of focus of the Unidad Editorial, publisher of a set of leading digital newspapers in Spain, including elmundo.es. The company ceased perceiving other digital newspapers as its competitor and tried to learn from the advertising revenue models of major players in the digital arena. This study argues that the management of big data is deeply transforming legacy newspapers' advertising regime. Their advertising model is increasingly based on more sophisticated segmentation tools and programmatic advertising techniques. It finds that a strategy to attract revenue based on learning from competitive models of big platforms is efficient and logical. Hence, the ability to market the value of individual users in real-time is a key factor in the success of this model.

scholarly journals Not a Mirror, but an Engine: Digital Methods for Contextual Analysis of “Social Big Data”

2021 ◽  
pp. 23-47
Author(s):  
Jonas Andersson Schwarz
Keyword(s):  
Big Data ◽  
Digital Media ◽  
Language Processing ◽  
Network Topology ◽  
Word Meanings ◽  
Social Big Data ◽  
Contextual Understanding ◽  
Recent Developments ◽  
Digital Methods ◽  
Social Scientific

Digital media infrastructures give rise to texts that are socially interconnected in various forms of complex networks. These mediated phenomena can be analyzed through methods that trace relational data. Social network analysis (SNA) traces interconnections between social nodes, while natural language processing (NLP) traces intralinguistic properties of the text. These methods can be bracketed under the header “social big data.” Empirical and theoretical rigor begs a constructionist understanding of such data. Analysis is inherently perspective-bound; it is rarely a purely objective statistical exercise. Some kind of selection is always made, primarily out of practical necessity. Moreover, the agents observed (network participants producing the texts in question) all tend to make their own encodings, based on observational inferences, situated in the network topology. Recent developments in such methods have, for example, provided social scientific scholars with innovative means to address inconsistencies in comparative surveys in different languages, addressing issues of comparability and measurement equivalence. NLP provides novel, inductive ways of understanding word meanings as a function of their relational placement in syntagmatic and paradigmatic relations, thereby identifying biases in the relative meanings of words. Reflecting on current research projects, the chapter addresses key epistemological challenges in order to improve contextual understanding.

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