Signal Crimes, Social Reactions, and the Future of Environmental Criminology

2018 ◽  
Author(s):  
Martin Innes ◽  
Helen Innes
Keyword(s):  
Social Media ◽  
Big Data ◽  
Social Control ◽  
Information Environment ◽  
Environmental Criminology ◽  
Unit Of Analysis ◽  
Conceptual Apparatus ◽  
Space And Time ◽  
The Future ◽  
Event Based

This chapter examines the precepts associated with the signal crimes perspective (SCP). It begins by setting out that a signal is something that transmits messages to an audience. Thinking in terms of signals and “signaling” opens up new ways of seeing crime, disorder, and social control. In particular, it keys into an event-based unit of analysis, as opposed to measuring impacts in an aggregated form. Having laid out the conceptual apparatus of the SCP, the discussion proceeds on to briefly consider how SCP compares with more established criminological frameworks for studying reactions to and consequences of crime. The latter sections of the chapter focus on the ways that changes to the information environment, associated with an era of “big data” and social media, are altering the incidents that signal and how their impacts travel across space and time.

Big Data and Clustering Techniques

2020 ◽  
pp. 1-9
Author(s):  
Jayashree K. ◽  
Chithambaramani R.
Keyword(s):  
Social Media ◽  
Big Data ◽  
Sensor Data ◽  
Log Data ◽  
Clustering Techniques ◽  
Research Challenges ◽  
The Future ◽  
Process Operations ◽  
Future Direction

Big data has become a chief strength of innovation across academics, governments, and corporates. Big data comprises massive sensor data, raw and semi-structured log data of IT industries, and the exploded quantity of data from social media. Big data needs big storage, and this volume makes operations such as analytical operations, process operations, retrieval operations very difficult and time consuming. One way to overcome these difficult problems is to have big data clustered in a compact format. Thus, this chapter discusses the background of big data and clustering. It also discusses the various application of big data in detail. The various related work, research challenges of big data, and the future direction are addressed in this chapter.

scholarly journals Language about the future on social media as a novel marker of anxiety and depression: A big-data and experimental analysis

2021 ◽  
Author(s):  
Cole Robertson ◽  
James Carney ◽  
Shane Trudel
Keyword(s):  
Social Media ◽  
Big Data ◽  
Temporal Discounting ◽  
Anxiety And Depression ◽  
Future Tense ◽  
Future Time ◽  
Theoretical Frameworks ◽  
Time Horizons ◽  
The Future ◽  
Future Events

Anxiety and depression are mood disorders which negatively impact many people. Psychology studies suggest depression is associated with future time horizons, or how "far" into the future people tend to think, and anxiety is associated with temporal discounting, or how much people devalue delayed future rewards. Separate studies from linguistics and economics have shown that individual differences in how people refer to future time predict temporal discounting. Yet no one—that we know of—has investigated whether future time reference habits are a marker of anxiety and/or depression. In Study 1, we analysed data from the social media website Reddit to test for relationships between these variables. Users who had previously posted popular contributions to forums dedicated to anxiety and depression referenced the future and the past more often than controls, had more proximal future and past time horizons, and significantly differed in their linguistic future time reference patterns. They used fewer future tense constructions (e.g. will), fewer high-certainty constructions (e.g. certainly), more low-certainty constructions (e.g. could), more bouletic modal constructions (e.g. hope), and more deontic modal constructions (e.g. must). This motivated Study 2, a survey-based mediation analysis. Self-reported anxious participants represented future events as more temporally distal and therefore temporally discounted to a greater degree. The same was not true of depression. We contextualise the results using two theoretical frameworks: construal level theory and functionalist approaches to clinical psychology. We conclude that methods which combine big-data with experimental paradigms can help identify novel markers of mental illness, which can aid in the development of new therapies and diagnostic criteria.

scholarly journals The future of the International Schools for Young Astronomers (ISYA)

2018 ◽  
Vol 13 (S349) ◽  
pp. 452-458 ◽  
Author(s):  
Itziar Aretxaga
Keyword(s):  
Machine Learning ◽  
Social Media ◽  
Big Data ◽  
International Schools ◽  
Virtual Networks ◽  
Internet Connectivity ◽  
New Era ◽  
Face To Face ◽  
The Future ◽  
Fast Internet

AbstractThe 5-decade old ISYA program is evaluated in the context of the experience gathered in the field: 41 schools organized in 27 countries with a total of more than 1400 students to date. In the new era of fast internet connectivity, social media, virtual networks, big data and machine learning, the value of face-to-face graduate schools for regions with limited up-to-date astrophysics research is presented, together with the plan to develop the ISYA program into the next decade.

scholarly journals Sentiment Computing for the News Event Based on the Social Media Big Data

IEEE Access ◽  
2017 ◽  
Vol 5 ◽  
pp. 2373-2382 ◽  
Author(s):  
Dandan Jiang ◽  
Xiangfeng Luo ◽  
Junyu Xuan ◽  
Zheng Xu
Keyword(s):  
Social Media ◽  
Big Data ◽  
The Social ◽  
News Event ◽  
Event Based ◽  
Sentiment Computing

Social Media Marketing as a tool to promote regional investment web portals in the information environment

2020 ◽  
Vol 18 (11) ◽  
pp. 2167-2182
Author(s):  
Ya.Yu. Sokolenko
Keyword(s):  
Social Media ◽  
Development Strategy ◽  
Information Environment ◽  
Social Media Marketing ◽  
Web Portals ◽  
Communication Tool ◽  
Web Portal ◽  
Investment Projects ◽  
Regional Investment ◽  
Internet Portals

Subject. This article focuses on the investment web portal as a necessary communication tool and a way to govern the investment attractiveness of the region. Objectives. The article aims to conduct a comprehensive study of the problem of promoting regional investment web portals in the information environment. Methods. For the study, I used the methods of logical and statistical analyses, induction and deduction, comparison, and generalization. Results. The article describes the advantages of Internet portals of investment projects and the peculiarities of using Social Media Marketing (SMM) within public structures. It highlights the function of social networks in the process of interacting with the audience. Conclusions. Social Media Marketing is an integral tool for engaging with the investment community and one of the most effective ways to promote a regional investment web portal. The presented original methodology can be used by regional investment portals to analyze interaction with the audience and design a development strategy.

Artistic Challenges within Control Societies: Big Data and Democratic Resistance

MedienJournal ◽  
2017 ◽  
Vol 38 (4) ◽  
pp. 50-61 ◽  
Author(s):  
Jan Jagodzinski
Keyword(s):  
Big Data ◽  
Gilles Deleuze ◽  
Data Archive ◽  
Current State ◽  
The Future ◽  
The Way

This paper will first briefly map out the shift from disciplinary to control societies (what I call designer capitalism, the idea of control comes from Gilles Deleuze) in relation to surveillance and mediation of life through screen cultures. The paper then shifts to the issues of digitalization in relation to big data that have the danger of continuing to close off life as zoë, that is life that is creative rather than captured via attention technologies through marketing techniques and surveillance. The last part of this paper then develops the way artists are able to resist the big data archive by turning the data in on itself to offer viewers and participants a glimpse of the current state of manipulating desire and maintaining copy right in order to keep the future closed rather than being potentially open.

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