The Social Internet of Things (SIoT) – When social networks meet the Internet of Things: Concept, architecture and network characterization

2012 ◽  
Vol 56 (16) ◽  
pp. 3594-3608 ◽  
Author(s):  
Luigi Atzori ◽  
Antonio Iera ◽  
Giacomo Morabito ◽  
Michele Nitti
Keyword(s):  
Social Networks ◽  
Internet Of Things ◽  
The Internet ◽  
The Social ◽  
Social Internet Of Things ◽  
Network Characterization ◽  
The Internet Of Things

Social Internet of Things in Healthcare

2017 ◽  
pp. 88-111 ◽  
Author(s):  
Cristina Elena Turcu ◽  
Corneliu Octavian Turcu
Keyword(s):  
Social Networks ◽  
Internet Of Things ◽  
Agent Technology ◽  
Smart Devices ◽  
Collaborative Environments ◽  
The Social ◽  
Social Internet Of Things ◽  
New Applications ◽  
Future Vision

This chapter presents a future vision for healthcare, which will involve smart devices, Internet of Things, and social networks, that make this vision a reality. The authors present the necessary background by introducing the Social Internet of Things paradigm. Agent technology seems to be a promising approach in the adoption of the Social Internet of Things in collaborative environments with increased autonomy and agility, like healthcare is. Also, it is examined challenges to the adoption of the Social Internet of Things in healthcare in order to facilitate new applications and services in more effective and efficient ways.

scholarly journals Building Topic-Driven Virtual IoTs in a Multiple IoTs Scenario

Sensors ◽  
2019 ◽  
Vol 19 (13) ◽  
pp. 2956 ◽  
Author(s):  
Paolo Lo Giudice ◽  
Antonino Nocera ◽  
Domenico Ursino ◽  
Luca Virgili
Keyword(s):  
Social Networks ◽  
Internet Of Things ◽  
Social Networking ◽  
Virtual Communities ◽  
The Internet ◽  
The Real ◽  
Challenging Issue ◽  
The One ◽  
The Internet Of Things ◽  
Made In

In the last years, several attempts to combine the Internet of Things (IoT) and social networking have been made. In the meantime, things involved in IoT are becoming increasingly sophisticated and intelligent, showing a behavior that tends to look like the one of users in social networks. Therefore, it is not out of place to talk about profiles of things and about information and topics exchanged among them. In such a context, constructing topic-driven virtual communities starting from the real ones operating in a Multi-IoT scenario is an extremely challenging issue. This paper aims at providing some contributions in this setting. First of all, it presents the concept of profile of a thing. Then, it introduces the concept of topic-guided virtual IoT. Finally, it illustrates two approaches (one supervised and one unsupervised) to constructing topic-guided virtual IoTs in a Multi-IoT scenario.

scholarly journals Concept, Possibilities and Pilot-Testing of a New Smartphone Application for the Social and Life Sciences to Study Human Behavior Including Validation Data from Personality Psychology

J ◽  
2019 ◽  
Vol 2 (2) ◽  
pp. 102-115 ◽  
Author(s):  
Christian Montag ◽  
Harald Baumeister ◽  
Christopher Kannen ◽  
Rayna Sariyska ◽  
Eva-Maria Meßner ◽  
...  
Keyword(s):  
Internet Of Things ◽  
Human Behavior ◽  
Real Life ◽  
Smartphone Application ◽  
Self Report ◽  
The Internet ◽  
Validation Data ◽  
Personality Psychology ◽  
The Social ◽  
The Internet Of Things

With the advent of the World Wide Web, the smartphone and the Internet of Things, not only society but also the sciences are rapidly changing. In particular, the social sciences can profit from these digital developments, because now scientists have the power to study real-life human behavior via smartphones and other devices connected to the Internet of Things on a large-scale level. Although this sounds easy, scientists often face the problem that no practicable solution exists to participate in such a new scientific movement, due to a lack of an interdisciplinary network. If so, the development time of a new product, such as a smartphone application to get insights into human behavior takes an enormous amount of time and resources. Given this problem, the present work presents an easy way to use a smartphone application, which can be applied by social scientists to study a large range of scientific questions. The application provides measurements of variables via tracking smartphone–use patterns, such as call behavior, application use (e.g., social media), GPS and many others. In addition, the presented Android-based smartphone application, called Insights, can also be used to administer self-report questionnaires for conducting experience sampling and to search for co-variations between smartphone usage/smartphone data and self-report data. Of importance, the present work gives a detailed overview on how to conduct a study using an application such as Insights, starting from designing the study, installing the application to analyzing the data. In the present work, server requirements and privacy issues are also discussed. Furthermore, first validation data from personality psychology are presented. Such validation data are important in establishing trust in the applied technology to track behavior. In sum, the aim of the present work is (i) to provide interested scientists a short overview on how to conduct a study with smartphone app tracking technology, (ii) to present the features of the designed smartphone application and (iii) to demonstrate its validity with a proof of concept study, hence correlating smartphone usage with personality measures.

scholarly journals Inequalities in the social use of the Internet of things: A capital and skills perspective

2019 ◽  
Vol 21 (6) ◽  
pp. 1344-1361 ◽  
Author(s):  
Alex van der Zeeuw ◽  
Alexander JAM van Deursen ◽  
Giedo Jansen
Keyword(s):  
Internet Of Things ◽  
Social Relations ◽  
The Internet ◽  
Internet Skills ◽  
The Social ◽  
Use Of The Internet ◽  
Social Use ◽  
Smart Things ◽  
Social Uses ◽  
The Internet Of Things

In this article, we set out to explain different types of social uses of the Internet of Things (IoT) using forms of capital and Internet skills. We argue that the IoT platform entices different manners of social communication that are easily overlooked when focusing on the novelty of smart “things.” How people use the IoT socially is crucial in trying to understand how people create, maintain, or absolve social relations in a networked society. We find inversed effects for social capital, income and education on private use, and on sharing IoT data with a partner. Sharing with acquaintances and strangers is predicted by cultural activities. Sharing IoT data with acquaintances can especially be attributed to social relations that escape the immediate household. We conclude that varying figurations of capital and Internet skills predict how the IoT is used socially.

scholarly journals How the Internet of Things Changes Everything

2020 ◽  
Vol 2 (4) ◽  
pp. 12
Author(s):  
Kate Carruthers
Keyword(s):  
Internet Of Things ◽  
The Internet ◽  
Social Web ◽  
Privacy And Security ◽  
Digital Revolution ◽  
Potential Value ◽  
The Social ◽  
The Internet Of Things ◽  
Insight Into ◽  
Convergence Of Technologies

In many ways the Internet of Things will change everything, as devices and software mesh and become part of the connected fabric of the Internet. This article explores the context and potential offered by the growth of the Internet of Things (IoT). It provides an overview of this next phase of the digital revolution that is underpinned by the growth of the social web, web 2.0, and the convergence of technologies such as mobile and ubiquitous broadband. This article also attempts to provide some insight into the potential value of the Internet of Things market in the future. The opportunities offered by the Internet of Things also raise serious questions about privacy and security in a connected world. As Umair Haque noted recently: “At some point, we should all question the value of an internet that objectifies you, tracks you, and polices you...without your consent.” (Haque 2014)

The Internet of Things

2020 ◽  
Author(s):  
Scott J. Shackelford
Keyword(s):  
Internet Of Things ◽  
Smart Devices ◽  
Stock Exchanges ◽  
The Internet ◽  
Internet Of Everything ◽  
The Social ◽  
Challenges And Opportunities ◽  
Perverse Incentives ◽  
And Control ◽  
The Internet Of Things

The Internet of Things (IoT) is the notion that nearly everything we use, from gym shorts to streetlights, will soon be connected to the Internet; the Internet of Everything (IoE) encompasses not just objects, but the social connections, data, and processes that the IoT makes possible. Industry and financial analysts have predicted that the number of Internet-enabled devices will increase from 11 billion to upwards of 75 billion by 2020. Regardless of the number, the end result looks to be a mind-boggling explosion in Internet connected stuff. Yet, there has been relatively little attention paid to how we should go about regulating smart devices, and still less about how cybersecurity should be enhanced. Similarly, now that everything from refrigerators to stock exchanges can be connected to a ubiquitous Internet, how can we better safeguard privacy across networks and borders? Will security scale along with this increasingly crowded field? Or, will a combination of perverse incentives, increasing complexity, and new problems derail progress and exacerbate cyber insecurity? For all the press that such questions have received, the Internet of Everything remains a topic little understood or appreciated by the public. This volume demystifies our increasingly “smart” world, and unpacks many of the outstanding security, privacy, ethical, and policy challenges and opportunities represented by the IoE. Scott J. Shackelford provides real-world examples and straightforward discussion about how the IoE is impacting our lives, companies, and nations, and explain how it is increasingly shaping the international community in the twenty-first century. Are there any downsides of your phone being able to unlock your front door, start your car, and control your thermostat? Is your smart speaker always listening? How are other countries dealing with these issues? This book answers these questions, and more, along with offering practical guidance for how you can join the effort to help build an Internet of Everything that is as secure, private, efficient, and fun as possible.

scholarly journals Towards Trust and Friendliness Approaches in the Social Internet of Things

2019 ◽  
Vol 9 (1) ◽  
pp. 166 ◽  
Author(s):  
Farhan Amin ◽  
Awais Ahmad ◽  
Gyu Sang Choi
Keyword(s):  
Internet Of Things ◽  
Reliable Data ◽  
Cloud Services ◽  
Interconnected Network ◽  
Common Goal ◽  
Embedded Devices ◽  
Social Contacts ◽  
The Social ◽  
Social Internet Of Things ◽  
The Internet Of Things

The Internet of Things (IoT) is an interconnected network of heterogeneous entities, such as sensors and embedded devices. During the current era, a new field of research has emerged, referred to as the social IoT, which mainly includes social networking features. The social IoT refers to devices that are capable of creating interactions with each other to independently achieve a common goal. Based on the structure, the support of numerous applications, and networking services, the social IoT is preferred over the traditional IoT. However, aspects like the roles of users and network navigability are major challenges that provoke users’ fears of data disclosure and privacy violations. Thus, it is important to provide reliable data analyses by using trust- and friendliness-based properties. This study was designed because of the limited availability of information in this area. It is a classified catalog of trust- and friendliness-based approaches in the social IoT with important highlights of important constraints, such as scalability, adaptability, and suitable network structures (for instance, human-to-human and human-to-object). In addition, typical concerns like communities of interest and social contacts are discussed in detail, with particular emphasis on friendliness- and trust-based properties, such as service composition, social similarity, and integrated cloud services.

scholarly journals Community privacy estimation method based on key node method in space social Internet of Things

2019 ◽  
Vol 15 (10) ◽  
pp. 155014771988313 ◽  
Author(s):  
Guobin Chen ◽  
Tangsen Huang
Keyword(s):  
Social Network ◽  
Internet Of Things ◽  
Estimation Method ◽  
Public Information ◽  
Clustering Coefficient ◽  
The Internet ◽  
The Core ◽  
Social Internet Of Things ◽  
Internet Of Things Technology ◽  
The Internet Of Things

Based on the research of social network and the Internet of Things, a new research topic in the field of Internet of Things, Social Internet of Things is gradually formed. The SIoT applies the research results of SIoT from different aspects of the Internet of Things, and solves the specific problems in the research of Internet of Things, which brings new opportunities for the development of the Internet of Things. With the development of the Internet of Things technology, in the spatial social Internet of Things structure, user information includes sensitive attributes and non-sensitive attribute information. This information can be inferred from public user information to infer the information of the private user and even speculate on sensitive attributes. This article proposes an information speculation method based on the core users of spatial social networks, and estimates the non-core user information through the core user public information. First, the user’s spatial social network is divided into communities, and the core nodes of the community in the spatial social network are calculated by PageRank algorithm and the convergence of the algorithm is proved. Then, through the public information of the core nodes divided by the community in the space social network, the private information of relevant users to these core nodes can be speculated. Finally, by experimental analyzing the community structures of SIoT (Social Internet of Things) like Twitter, Sina Weibo, ER random networks, and NW small-world network, and making 5%, 10%, 15%, 20% information anonymous respectively in these four kinds of networks, we can analyze their clustering coefficient, Q-modularity and properties. Finally, the key node information of the four spatial social structures is speculated to analyze the effectiveness of the proposed method. Compared with the non-core speculation method, this method has advantages in speculative information integrity and time.

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