scholarly journals Identifying Influencers in Social Networks

Entropy ◽  
2020 ◽  
Vol 22 (4) ◽  
pp. 450 ◽  
Author(s):  
Xinyu Huang ◽  
Dongming Chen ◽  
Dongqi Wang ◽  
Tao Ren
Keyword(s):  
Social Networks ◽  
Social Media ◽  
Social Network ◽  
Daily Life ◽  
Multidisciplinary Research ◽  
Multilayer Network ◽  
Online Social Media ◽  
Huge Data ◽  
Real World Datasets ◽  
Shed Light

Social network analysis is a multidisciplinary research covering informatics, mathematics, sociology, management, psychology, etc. In the last decade, the development of online social media has provided individuals with a fascinating platform of sharing knowledge and interests. The emergence of various social networks has greatly enriched our daily life, and simultaneously, it brings a challenging task to identify influencers among multiple social networks. The key problem lies in the various interactions among individuals and huge data scale. Aiming at solving the problem, this paper employs a general multilayer network model to represent the multiple social networks, and then proposes the node influence indicator merely based on the local neighboring information. Extensive experiments on 21 real-world datasets are conducted to verify the performance of the proposed method, which shows superiority to the competitors. It is of remarkable significance in revealing the evolutions in social networks and we hope this work will shed light for more and more forthcoming researchers to further explore the uncharted part of this promising field.

Working Adults' Buying Intention Through Online Social Network

2021 ◽  
Vol 17 (4) ◽  
pp. 92-116
Author(s):  
Syed Shah Alam ◽  
Chieh-Yu Lin ◽  
Mohd Helmi Ali ◽  
Nor Asiah Omar ◽  
Mohammad Masukujjaman
Keyword(s):  
Social Networks ◽  
Social Media ◽  
Social Network ◽  
Online Social Networks ◽  
Perceived Risk ◽  
Word Of Mouth ◽  
Online Social Network ◽  
Perceived Value ◽  
Online Social Media ◽  
Starting Point

Most businesses have online social media presence; therefore, understanding of working adult's perception on buying through online social networks is vital. The aim of this study is to examine the effect of perceived value, sociability, usability, perceived risk, trust, and e-word-of-mouth on buying intention through online social network sites. The research model for this study was developed based on the literature on information system research. This study adopted convenient sampling of non-probability sampling procedure. Data were collected through self-administered questionnaire, and PLS-based path analysis was used to analyse responses. The findings of the study shows that perceived value, sociability, usability, e-word-of-mouth, attitude, and subjective norm are significant constructs of buying intention through online social networks. This research can serve as a starting point for online shopping research through online social media while encouraging further exploration and integration addition adoption constructs.

A Study Regarding Human Perception of a Company through Social Media

2019 ◽  
Vol 34 ◽  
pp. 309-314
Author(s):  
Mirona Ana Maria Popescu ◽  
Olivia Doina Negoiță ◽  
Anca Purcărea ◽  
Markus Helfert
Keyword(s):  
Social Networks ◽  
Social Media ◽  
Social Network ◽  
Human Perception ◽  
Social Media Networks ◽  
Online Social Media ◽  
The Social ◽  
Key Indicators ◽  
Different Characteristics ◽  
A Company

Of the utmost importance is finding the social networks that best fit to an industry, a company, its products / services, and last but not least, with the target audience. Each social network has different characteristics and, in addition, a different philosophy.The authors aim to carry out a bibliographic research in this paper to highlight the extent to which social networks are used. As a result, a top of social networks will be built to help raise awareness, promote products, and consolidate a strong customer-company relationship. The authors will also realize a statistical analysis of online social media networks to determine their key indicators, traffic on each platform, time spent by a user on that platform, and other key indicators, through an online tool. The results of this paper consist in presenting two classifications: the first from the perspective of the companies and the second from the perspective of social network users.

scholarly journals Searching and sharing of information in social networks during the different stages of a trip

2018 ◽  
pp. 185-212 ◽  
Author(s):  
Assumpció Huertas ◽  
Estela Marine-Roig
Keyword(s):  
Social Networks ◽  
Social Media ◽  
Social Network ◽  
Online Social Media ◽  
The Social ◽  
Use Of Social Media ◽  
The Relationship ◽  
Source Of Information ◽  
Share Information ◽  
Three Phases

There are three phases in the use of online social media by tourists: before, during and after the trip. The aim of this study is to determine what social network users use to find information before and during the trip, the type of information they search, and where they share information. The study also identifies the relationship this has with the trustworthiness social networks provide them, especially distinguishing the social networks managed by the destination organizations. Therefore, we conduct a survey of 800 tourists who are social network users. Results show that social networks are not a major source of information before or during the trip but are very important for sharing contents after the experience, and that the most searched information concerns the main attractions of the destination. Moreover, there is a relationship between the use of social media and their perceived trustworthiness. In this case, for those who use social networks managed by destinations, these give them greater confidence.

Emotive Trending And Tracking of Tweets

2017 ◽  
Vol 7 (11) ◽  
pp. 25
Author(s):  
Sanjay Chhataru Gupta
Keyword(s):  
Social Networks ◽  
Social Media ◽  
Social Network ◽  
The Social ◽  
The World ◽  
Complex Events

Popularity of the social media and the amount of importance given by an individual to social media has significantly increased in last few years. As more and more people become part of the social networks like Twitter, Facebook, information which flows through the social network, can potentially give us good understanding about what is happening around in our locality, state, nation or even in the world. The conceptual motive behind the project is to develop a system which analyses about a topic searched on Twitter. It is designed to assist Information Analysts in understanding and exploring complex events as they unfold in the world. The system tracks changes in emotions over events, signalling possible flashpoints or abatement. For each trending topic, the system also shows a sentiment graph showing how positive and negative sentiments are trending as the topic is getting trended.

scholarly journals I Know Where You Are Coming From: On the Impact of Social Media Sources on AI Model Performance (Student Abstract)

2020 ◽  
Vol 34 (10) ◽  
pp. 13971-13972
Author(s):  
Yang Qi ◽  
Farseev Aleksandr ◽  
Filchenkov Andrey
Keyword(s):  
Machine Learning ◽  
Social Networks ◽  
Social Media ◽  
Social Network ◽  
Model Performance ◽  
User Profiling ◽  
Personalized Recommendation ◽  
Modal Data ◽  
Social Media Networks ◽  
The Impact

Nowadays, social networks play a crucial role in human everyday life and no longer purely associated with spare time spending. In fact, instant communication with friends and colleagues has become an essential component of our daily interaction giving a raise of multiple new social network types emergence. By participating in such networks, individuals generate a multitude of data points that describe their activities from different perspectives and, for example, can be further used for applications such as personalized recommendation or user profiling. However, the impact of the different social media networks on machine learning model performance has not been studied comprehensively yet. Particularly, the literature on modeling multi-modal data from multiple social networks is relatively sparse, which had inspired us to take a deeper dive into the topic in this preliminary study. Specifically, in this work, we will study the performance of different machine learning models when being learned on multi-modal data from different social networks. Our initial experimental results reveal that social network choice impacts the performance and the proper selection of data source is crucial.

scholarly journals Digital sources: a case study of the analysis of the Recovery of Historical Memory in Spain on the social network Twitter

2019 ◽  
Vol 7 (2) ◽  
pp. 015 ◽  
Author(s):  
Mariluz Congosto
Keyword(s):  
Data Mining ◽  
Social Media ◽  
Social Network ◽  
Historical Memory ◽  
Historical Research ◽  
Huge Amount ◽  
Online Social Media ◽  
The Social ◽  
Special Relevance

The incorporation of digital sources from online social media into historical research brings great opportunities, although it is not without technological challenges. The huge amount of information that can be obtained from these platforms obliges us to resort to the use of quantitative methodologies in which algorithms have special relevance, especially regarding network analysis and data mining. The Recovery of Historical Memory in Spain on the social network Twitter will be analysed in this article. An open-code tool called T-Hoarder was used; it is based on objectivity, transparency and knowledge-sharing. It has been in use since 2012.

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.

scholarly journals tugas review artikel

2019 ◽  
Author(s):  
Arlika Anindya Putri
Keyword(s):  
Social Capital ◽  
Social Networks ◽  
Social Media ◽  
Social Network ◽  
Firm Performance ◽  
Positive Impact ◽  
Social Capital Theory ◽  
Capital Theory ◽  
Mediating Role ◽  
The Social

Purpose – The purpose of this study is to develop a structural equation model to explain the complexrelationship between social network and firm performance by introducing the mediating role of trust, sellingcapability and pricing capability.Design/methodology/approach – The research model with hypothesis development was derived basedon the literature. To provide empirical evidence, this study carried out a survey in which the data wereequated with a list of questionnaires with a random survey of 380 small and medium enterprises (SMEs) inthe Indonesian context.Findings – This study indicates that the use of social media in management process will not affect theincreasing firm performance, unless the firms build trust upon social networks. The social network with trustallows the firms to gain a pricing capability and a selling capability, which brings a positive impact on firmperformance. The results also show that the selling and the pricing capabilities become essential following theutilizing the social media, which concerns on trust building.Research limitations/implications – This study focused on the small-to-medium context, which hasconventionally provided an exemplary site for the development of social capital theory but raises issues ofgeneralizability across different contexts.Practical implications – To the managers, it is advisable to encourage their employees to consciouslyexploit the selling capability by enhancing the business networks via social media to achieve the firmperformance.Originality/value – This paper contributes to the social capital theory by explaining the mediating role oftrust in the complex relationship between social network and firm performance. This study provides evidencethat trust plays a pivotal role in social networks, which enable the observed firms to achieve the performance.

Socio-Technical Attack Approximation Based on Structural Virality of Information in Social Networks

2021 ◽  
Vol 15 (1) ◽  
pp. 153-172
Author(s):  
Preetish Ranjan ◽  
Abhishek Vaish
Keyword(s):  
Social Networks ◽  
Social Media ◽  
Social Network ◽  
Latent Structure ◽  
The Social ◽  
High Skill ◽  
The Way

A free and easily accessible platform for sharing information over social media has its negatives. It is being misused to intimidate others by exploiting the trust factor inherent within it. This paper is on the persistent pursuit of offering an exquisite solution to address this possible misuse of social media also called STAs and their subsequent impacts on society. These attacks are very sensitive to society and often organized groups with a high skill set are involved to disguise the security agencies. In this work, a model has been proposed to approximate socio-technical attack subject to the structural virality of information in the social network. The work is unique in the sense that previous works are mostly based on statistical values of the network but the proposed work considers the latent structure of the network which is not being reflected from their statistical values. This also paves the way for future researchers to implant other hidden features of nodes and messages circulating within the network which could be helpful for the detection and mitigation of STAs.

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