Using Social Network to Support Smart City Initiatives

2015 ◽  
Author(s):  
Mickael Figueredo ◽  
José Ribeiro ◽  
Arthur Emanuel ◽  
Andréa Cacho ◽  
Hiarley Farias ◽  
...  
Keyword(s):  
Social Network ◽  
Smart City

scholarly journals Research on Sentiment Tendency and Evolution of Public Opinions in Social Networks of Smart City

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-13 ◽  
Author(s):  
Yanni Liu ◽  
Dongsheng Liu ◽  
Yuwei Chen
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Sentiment Analysis ◽  
Smart City ◽  
Topic Model ◽  
Rapid Development ◽  
Mobile Internet ◽  
Time Curve ◽  
Public Opinions ◽  
The Social

With the rapid development of mobile Internet, the social network has become an important platform for users to receive, release, and disseminate information. In order to get more valuable information and implement effective supervision on public opinions, it is necessary to study the public opinions, sentiment tendency, and the evolution of the hot events in social networks of a smart city. In view of social networks’ characteristics such as short text, rich topics, diverse sentiments, and timeliness, this paper conducts text modeling with words co-occurrence based on the topic model. Besides, the sentiment computing and the time factor are incorporated to construct the dynamic topic-sentiment mixture model (TSTS). Then, four hot events were randomly selected from the microblog as datasets to evaluate the TSTS model in terms of topic feature extraction, sentiment analysis, and time change. The results show that the TSTS model is better than the traditional models in topic extraction and sentiment analysis. Meanwhile, by fitting the time curve of hot events, the change rules of comments in the social network is obtained.

scholarly journals RE-ENGINEERING OF SMART CITY'S BUSINESS PROCESSES BASED ON SOCIAL NETWORKS AND INTERNET OF THINGS

2018 ◽  
Vol 16 (3) ◽  
pp. 275
Author(s):  
Emir Ugljanin ◽  
Dragan Stojanović ◽  
Ejub Kajan ◽  
Zakaria Maamar
Keyword(s):  
Social Networks ◽  
Social Media ◽  
Social Network ◽  
Internet Of Things ◽  
Smart City ◽  
Business Processes ◽  
Smart Cities ◽  
Successful Management ◽  
Complete Integration ◽  
Social Actions

This paper reports our experience with developing a Business-2-Social (B2S) platform that provides necessary support to all this platform’s constituents, namely business processes, social media (e.g., social network), and Internet of Things (IoT). This platform is exemplified with smart cities whose successful management requires a complete integration of IoT and social media capabilities into the business processes implementing user services. To ensure a successful integration, social actions, that a smart city would allow citizens execute, are analyzed in terms of impact of these smart city’s business processes. Reactions to these actions are tracked and then analyzed to improve user services.

Autonomy-oriented proximity mobile social network modeling in smart city for emergency rescue

2021 ◽  
Vol 17 (12) ◽  
pp. 155014772110612
Author(s):  
Zhao Chunxiao ◽  
Guo Junjie
Keyword(s):  
Social Network ◽  
Network Model ◽  
Smart City ◽  
Disaster Relief ◽  
Network Modeling ◽  
Mobile Social Network ◽  
Emergency Rescue ◽  
Routing Strategy ◽  
Social Network Modeling ◽  
Post Disaster

Nearest neighbor mobile social network means that movers approaching in position communicate through their social sensors, which is called Proximity Mobile Social Network. Proximity Mobile Social Network can provide more social and business opportunities for users. To carry out disaster relief work in post-disaster environment, we need to collect incident information during the search process and report to the sink in time. Proximity Mobile Social Network provides flexible systems for emergency handling and disaster relief. Therefore, how to find a better data forwarding and routing strategy is the key problem of post-disaster rescue, and the research of user mobility model is the basis of the above problems. This article presents an Autonomy-Oriented Proximity Mobile Social Network modeling for emergency rescue in smart city, which simulates the network operating environment. First, we verify the performance of Autonomy-Oriented Proximity Mobile Social Network model in terms of self-organization, scale-free, aggregation, and community structure. Then, the rescue efficiency is discussed through the coverage of mobile sensors. Finally, performance of the routing strategy based on Autonomy-Oriented Proximity Mobile Social Network model is analyzed, and the effectiveness of the method is proved.

SONATA

2016 ◽  
Vol 7 (1) ◽  
pp. 59-78 ◽  
Author(s):  
Burak Kantarci ◽  
Kevin G. Carr ◽  
Connor D. Pearsall
Keyword(s):  
Social Network ◽  
Social Interactions ◽  
Smart City ◽  
Network Architecture ◽  
Crucial Issue ◽  
Detection Techniques ◽  
Dynamic Social Network ◽  
Computing Paradigm ◽  
Performance Results ◽  
Analyze Data

With the advent of mobile cloud computing paradigm, mobile social networks (MSNs) have become attractive tools to share, publish and analyze data regarding everyday behavior of mobile users. Besides revealing information about social interactions between individuals, MSNs can assist smart city applications through crowdsensing services. In presence of malicious users who aim at misinformation through manipulation of their sensing data, trustworthiness arises as a crucial issue for the users who receive service from smart city applications. In this paper, the authors propose a new crowdsensing framework, namely Social Network Assisted Trustworthiness Assurance (SONATA) which aims at maximizing crowdsensing platform utility and minimizing the manipulation probability through vote-based trustworthiness analysis in dynamic social network architecture. SONATA adopts existing Sybil detection techniques to identify malicious users who aim at misinformation/disinformation at the crowdsensing platform. The authors present performance evaluation of SONATA under various crowdsensing scenarios in a smart city setting. Performance results show that SONATA improves crowdsensing utility under light and moderate arrival rates of sensing task requests when less than 7% of the users are malicious whereas crowdsensing utility is significantly improved under all task arrival rates if the ratio of malicious users to the entire population is at least 7%. Furthermore, under each scenario, manipulation ratio is close to zero under SONATA while trustworthiness unaware recruitment of social network users leads to a manipulation probability of 2.5% which cannot be tolerated in critical smart city applications such as disaster management or public safety.

scholarly journals WeChat: Social Network and Smart City

2019 ◽  
Vol 2 (3) ◽  
pp. p11
Author(s):  
Jing Zhang ◽  
Cristobal Fernandez Muñoz ◽  
Liisa Irene Hänninen
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Detailed Analysis ◽  
Smart City ◽  
Instant Messaging ◽  
Rapid Expansion ◽  
Advanced Technology ◽  
Western World ◽  
Payment Method

The work focuses on the study of WeChat (main social network in China) and its digital activity for its advanced functionalities which build intelligent society in China. The importance of this platform lies in the prohibition of Western social networks in China.  For 7 years,  WeChat has evolved as a “super social network”, from an instant messaging application to a hybrid including application, marketplace, payment method and operating systemz, as an integrated means rather than just social network. In today's western world, almost no network can be compared with WeChat in terms of its functionalities. It is a good example of promotion and development of the intelligent society because of its advanced functionalities. The new usage and the rapid expansion of its integrated functionality and impacts form the new communication consumption framework in China. This work shows how an intelligent society changes and develops through a social network, and detailed analysis of advanced technology and social network of WeChat to give a good example to Westren countries which want to build intelligent society.

scholarly journals Analisis Kesiapan Masyarakat Pada Penerapan Smart City di Sosial Media Menggunakan SNA

2021 ◽  
Vol 5 (1) ◽  
pp. 69-81
Author(s):  
M. Khairul Anam ◽  
Tri Putri Lestari ◽  
Latifah ◽  
Muhammad Bambang Firdaus ◽  
Sofiansyah Fadli
Keyword(s):  
Social Media ◽  
Social Network ◽  
Network Analysis ◽  
Social Interactions ◽  
Smart City ◽  
The People ◽  
Twitter Users ◽  
The Government ◽  
The Relationship

Smart People, which means smart city residents or people, not only refers to one's education but also the quality of social interactions that are formed. This Social Network Analysis (SNA) emphasizes the relationship between actors / users rather than the attributes of these actors. This analysis aims to see whether the people of Pekanbaru are ready to face changes to a Smart City. Pekanbaru is a civil city that will build a Smart City, with a concept that adopts 6 pillars, one of which is Smart People. There are 720,000 Twitter users in Pekanbaru City, while the people who actively interact are only 227 users or around 0.031%. Meanwhile, a city that can be said to be ready should be around 60-80% of active users who provide opinions or comments to the government of Pekanbaru City. From this research, it can be concluded that the people of Pekanbaru City are not ready to face Smart City Madani as seen from the interaction of the community on social media Twitter.

scholarly journals Role of Big Data in the Development of Smart City by Analyzing the Density of Residents in Shanghai

Electronics ◽  
2020 ◽  
Vol 9 (5) ◽  
pp. 837 ◽  
Author(s):  
Saqib Ali Haidery ◽  
Hidayat Ullah ◽  
Naimat Ullah Khan ◽  
Kanwal Fatima ◽  
Sanam Shahla Rizvi ◽  
...  
Keyword(s):  
Social Network ◽  
Density Estimation ◽  
Kernel Density Estimation ◽  
Smart City ◽  
Kernel Density ◽  
Spatial Behavior ◽  
Estimation Techniques ◽  
Point Density ◽  
Location Based Social Network ◽  
Bivariate Density

In recent decades, a large amount of research has been carried out to analyze location-based social network data to highlight their application. These location-based social network datasets can be used to propose models and techniques that can analyze and reproduce the spatiotemporal structures and symmetries in user activities as well as density estimations. In the current study, different density estimation techniques are utilized to analyze the check-in frequency of users in more detail from location-based social network dataset acquired from Sina-Weibo, also referred as Weibo, over a specific period in 10 different districts of Shanghai, China. The aim of this study is to analyze the density of users in Shanghai city from geolocation data of Weibo as well as to compare their density through univariate and bivariate density estimation techniques; i.e., point density and kernel density estimation (KDE) respectively. The main findings of the study include the following: (i) characteristics of users’ spatial behavior, the center of activity based on their check-ins, (ii) the feasibility of check-in data to explain the relationship between users and social media, and (iii) the presentation of evident results for regulatory or managing authorities for urban planning. The current study shows that the point density and kernel density estimation. KDE methods provide useful insights for modeling spatial patterns using geo-spatial dataset. Finally, we can conclude that, by utilizing the KDE technique, we can examine the check-in behavior in more detail for an individual as well as broader patterns in the population as a whole for the development of smart city. The purpose of this article is to figure out the denser places so that the authorities can divide the mobility of people from the same routes or at least they can control the situation from any further inconvenience.

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