scholarly journals Social network analysis in Telecom data

2019 ◽  
Vol 6 (1) ◽  
Author(s):  
Nour Raeef Al-Molhem ◽  
Yasser Rahal ◽  
Mustapha Dakkak
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Prediction Models ◽  
Similarity Measures ◽  
Centrality Measures ◽  
Customer Data ◽  
Node Importance ◽  
Network Similarity ◽  
Telecom Network

AbstractMany systems can be represented as networks or graph collections of nodes joined by edges. The social structures in these networks can be investigated using graph theory through a process called social network analysis (SNA). In this paper, networks and SNA concepts were applied using Telecom data such as call detail records (CDRs) and customers data to model our social network and to construct a weighed graph in which each relation carries a different weight, representing how close two subscribers are to each other. In addition, SNA is used to explore the Telecom network and calculate the centrality measures, which help determine the node importance in the network. Depending on centrality measures as well as influence capability of node measure, the influencers in network were detected and targeted by marketing campaigns resulting in 30% raise in growth rate of mobile traffic compared with traditional ways. Finding Multi-SIM subscribers within the same operator or across different operators presents another important concern to Telecom companies because it allows to improve campaigns and churn prediction models. Social network similarity measures and social behavioral measures between nodes were calculated in the Telecom network to detect these Multi-SIM subscribes and 85% accuracy result was achieved for subscribes from different operators and 92% for subscribes from the same operator. The paper is based on a real dataset of 3 months CDRs and customer data provided by a local Telecom operator. This dataset is used to build a network with more than 16 million nodes and more than 300 million edges on a big data platform.

Use of Social Network Analysis in Telecommunication Domain

2018 ◽  
pp. 152-178 ◽  
Author(s):  
Sushruta Mishra ◽  
Brojo Kishore Mishra ◽  
Hrudaya Kumar Tripathy ◽  
Monalisa Mishra ◽  
Bijayalaxmi Panda
Keyword(s):  
Social Networks ◽  
Graph Theory ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
The Other ◽  
Centrality Measures ◽  
Customer Data ◽  
Relationship Types ◽  
Heterogeneous Social Networks

Social network analysis (SNA) is the analysis of social communication through network and graph theory. In our chapter the application of SNA has been explored in telecommunication domain. Telecom data consist of Customer data and Call Detail Data (CDR). The proposed work, considers the attributes of call detail data and customer data as different relationship types to model our Multi-relational Telecommunication social network. Typical work on social network analysis includes the discovery of group of customers who shares similar properties. A new challenge is the mining of hidden communities on such heterogeneous social networks, to group the customers as churners and non-churners in Telecommunication social network. After the analysis of the available data we constructed a Weights Multi-relational Social Network, in which each relation carry a different weight, representing how close two customers are with one another. The centrality measures depict the intensity of the customer closeness, hence we can determine the customer who influence the other customer to churn.

scholarly journals Visualization of clinical teaching citations using social network analysis

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Hakimeh Hazrati ◽  
Shoaleh Bigdeli ◽  
Seyed Kamran Soltani Arabshahi ◽  
Vahideh Zarea Gavgani ◽  
Nafiseh Vahed
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Research Collaboration ◽  
Clinical Teaching ◽  
Clustering Coefficient ◽  
Knowledge Network ◽  
Research Network ◽  
Centrality Measures ◽  
The Usa

Abstract Background Analyzing the previous research literature in the field of clinical teaching has potential to show the trend and future direction of this field. This study aimed to visualize the co-authorship networks and scientific map of research outputs of clinical teaching and medical education by Social Network Analysis (SNA). Methods We Identified 1229 publications on clinical teaching through a systematic search strategy in the Scopus (Elsevier), Web of Science (Clarivate Analytics) and Medline (NCBI/NLM) through PubMed from the year 1980 to 2018.The Ravar PreMap, Netdraw, UCINet and VOSviewer software were used for data visualization and analysis. Results Based on the findings of study the network of clinical teaching was weak in term of cohesion and the density in the co-authorship networks of authors (clustering coefficient (CC): 0.749, density: 0.0238) and collaboration of countries (CC: 0.655, density: 0.176). In regard to centrality measures; the most influential authors in the co-authorship network was Rosenbaum ME, from the USA (0.048). More, the USA, the UK, Canada, Australia and the Netherlands have central role in collaboration countries network and has the vertex co-authorship with other that participated in publishing articles in clinical teaching. Analysis of background and affiliation of authors showed that co-authorship between clinical researchers in medicine filed is weak. Nineteen subject clusters were identified in the clinical teaching research network, seven of which were related to the expected competencies of clinical teaching and three related to clinical teaching skills. Conclusions In order to improve the cohesion of the authorship network of clinical teaching, it is essential to improve research collaboration and co-authorship between new researchers and those who have better closeness or geodisk path with others, especially those with the clinical background. To reach to a dense and powerful topology in the knowledge network of this field encouraging policies to be made for international and national collaboration between clinicians and clinical teaching specialists. In addition, humanitarian and clinical reasoning need to be considered in clinical teaching as of new direction in the field from thematic aspects.

scholarly journals A case study of university student networks and the COVID-19 pandemic using a social network analysis approach in halls of residence

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
José Alberto Benítez-Andrades ◽  
Tania Fernández-Villa ◽  
Carmen Benavides ◽  
Andrea Gayubo-Serrenes ◽  
Vicente Martín ◽  
...  
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
University Students ◽  
Methodological Approach ◽  
Centrality Measures ◽  
Structural Behaviour ◽  
Cross Sectional ◽  
Depth Analysis ◽  
The University

AbstractThe COVID-19 pandemic has meant that young university students have had to adapt their learning and have a reduced relational context. Adversity contexts build models of human behaviour based on relationships. However, there is a lack of studies that analyse the behaviour of university students based on their social structure in the context of a pandemic. This information could be useful in making decisions on how to plan collective responses to adversities. The Social Network Analysis (SNA) method has been chosen to address this structural perspective. The aim of our research is to describe the structural behaviour of students in university residences during the COVID-19 pandemic with a more in-depth analysis of student leaders. A descriptive cross-sectional study was carried out at one Spanish Public University, León, from 23th October 2020 to 20th November 2020. The participation was of 93 students, from four halls of residence. The data were collected from a database created specifically at the university to "track" contacts in the COVID-19 pandemic, SiVeUle. We applied the SNA for the analysis of the data. The leadership on the university residence was measured using centrality measures. The top leaders were analyzed using the Egonetwork and an assessment of the key players. Students with higher social reputations experience higher levels of pandemic contagion in relation to COVID-19 infection. The results were statistically significant between the centrality in the network and the results of the COVID-19 infection. The most leading students showed a high degree of Betweenness, and three students had the key player structure in the network. Networking behaviour of university students in halls of residence could be related to contagion in the COVID-19 pandemic. This could be described on the basis of aspects of similarities between students, and even leaders connecting the cohabitation sub-networks. In this context, Social Network Analysis could be considered as a methodological approach for future network studies in health emergency contexts.

Social network analysis applications in sustainable construction and built environment management: a review

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Nandun Madhusanka Hewa Welege ◽  
Wei Pan ◽  
Mohan Kumaraswamy
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Built Environment ◽  
Methodological Approach ◽  
Relevant Literature ◽  
Sustainable Construction ◽  
Centrality Measures ◽  
Environment Management ◽  
Content Type

PurposeApplications of social network analysis (SNA) are evidently popular amongst scholars for mapping stakeholder and other relational networks in improving the sustainability of construction activities and the resulting built environment. Nevertheless, the literature reveals a lack of thorough understanding of optimal SNA applications in this field. Therefore, this paper aims to convey a comprehensive critical review of past applications of SNA in this field.Design/methodology/approach95 relevant journal papers were initially identified from the “Web of Science” database and a bibliometric analysis was carried out using the “VOS Viewer” software. The subsequent in-depth review of the SNA methods, focussed on 24 specifically relevant papers selected from these aforesaid 95 papers.FindingsA significant growth of publications in this field was identified after 2014, especially related to topics on stakeholder management. “Journal of Cleaner Production”, “International Journal of Project Management” and “Sustainability” were identified as the most productive sources in this field, with the majority of publications from China. Interviews and questionnaires were the popular data collection methods while SNA “Centrality” measures were utilised in over 70% of the studies. Furthermore, potential areas were noted, to improve the mapping and thereby provide useful information to managers who could influence relevant networks and consequentially better sustainability outcomes, including those enhanced by collaborative networks.Originality/valueCloser collaboration has been found to help enhance sustainability in construction and built environment, hence attracting research interest amongst scholars on how best to enable this. SNA is established as a significant methodological approach to analysing interrelationships and collaborative potential in general. In a pioneering application here, this paper initiates the drawing together of findings from relevant literature to provide useful insights for future researchers to comprehensively identify, compare and contrast the applications of SNA techniques in construction and built environment management from a sustainability viewpoint.

Social Network Analysis in Egyptology: Benefits, Methods and Limits

2019 ◽  
Vol 105 (1) ◽  
pp. 83-96
Author(s):  
Vincent Chollier
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Social Relationships ◽  
Empirical Method ◽  
Ancient Egypt ◽  
Centrality Measures ◽  
Defining Relations ◽  
The Family ◽  
Kinship Terminology

This article aims at presenting a methodology for Social Network Analysis (SNA) applied to Egyptology and ancient societies studies, with its benefits and issues. One of the big issues dealing with social relationships in ancient Egypt lies in the use of kinship terminology defining relations outside the family. In that sense, SNA allows researchers to partially set aside links values contrary to traditional genealogical studies, especially for the graphical projection. Thus, biological and social brothers do not have to be distinguished using this method, although this distinction is often impossible to do. It then presents an empirical method developed using this branch of sociology on an Egyptological dataset dating back from the New Kingdom. With the help of centrality measures, SNA enabled attention to be drawn to secondary role characters at the first sight of the hieroglyphic documentation. However, studying such a type of documentation requires a cautious approach, especially regarding the nature and aim of the sources available.

Centrality Measures and Academic Achievement in Computerized Classroom Social Networks

2017 ◽  
Vol 56 (4) ◽  
pp. 589-618 ◽  
Author(s):  
Iris Reychav ◽  
Daphne Ruth Raban ◽  
Roger McHaney
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Social Networking ◽  
Learning Task ◽  
Learning Performance ◽  
Centrality Measures ◽  
Group Consensus ◽  
Learning Assessments ◽  
Individual Assessment

The current empirical study examines relationships between network measures and learning performance from a social network analysis perspective. We collected computerized, networking data to analyze how 401 junior high students connected to classroom peers using text- and video-based material on iPads. Following a period of computerized interaction, learning assessments were taken at individual or group consensus levels. Social network analysis suggested highly connected students became information sources with higher individual assessment achievements. Students receiving information from central sources exhibited higher achievements in group consensus treatments. Students acting as bridges between others on the network regulated themselves better and achieved higher academic outcomes. However, a subset of students were motivated by social interaction rather than learning task. This finding, consistent with general social networking research, cautions educators to ensure socializing does not override learning objectives when using classroom social networking.

scholarly journals Identifying Disease Comorbidity Patterns Using Centrality Measures in Computing

2021 ◽  
Vol 11 (4) ◽  
pp. 2964-2975
Author(s):  
Zahra Batool ◽  
Muhammad Junaid ◽  
Muhammad Naeem ◽  
Mehmood Ahmed ◽  
Luqman Shah ◽  
...  
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Human Disease ◽  
Centrality Measures ◽  
Disease Network ◽  
Overlapping Communities ◽  
Crowd Management ◽  
Disease Networks ◽  
Business Modelling

Social network analysis has been increasingly employed to study patterns in diverse areas of disciplines such as crowd management, air passenger and freight transportation, business modelling and analysis, online social movements and bioinformatics. Over the years, human disease networks have been studied to analyze Human Disease, Genotype, and Phenotype networks. This study explores human Disease Network based on their symptoms by employing different social network analysis such as centrality measures of network, community detection, overlapping communities. We studied relationships of symptoms with diseases on meso-level in order to detect comorbidity pattern of communities in disease network. This help us to understand the underlying patterns of diseases based on symptoms and find out that how different disease communities are correlated by detecting overlapping communities.

scholarly journals The Effect Of The Relationships Between Affiliated Firms On Direction Of Income Shifting Within Business Groups

2014 ◽  
Vol 30 (3) ◽  
pp. 817 ◽  
Author(s):  
Kyung Jin Park ◽  
Joohyun Lim ◽  
Ki Young Kim
Keyword(s):  
Decision Making ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Ownership Structure ◽  
Business Group ◽  
The Other ◽  
Centrality Measures ◽  
Income Shifting ◽  
Tax Burden

<p>In this study, we examined how income shifting performs among affiliates in a business group to maximize the benefits of the entire business group in terms of minimizing the tax burden, with a particular focus on the direction of income shifting between affiliates within the business group. We find that tax-related decision-making for the entire business group is affected by the relationships between the affiliated firms, that is, the ownership structure of the whole business group. To analyze the ownership structure, we use centrality measures in a social network analysis. The results show that affiliates with the higher outdegree-centrality; that is, firms investing more shareholdings in other affiliates have a tendency to perform more income shifting. On the other hand, the affiliates with high indegree-centrality, that is, firms which are owned by other affiliates, were revealed to be given the income shifting from other affiliated firms to minimize the tax burden of the entire business group.</p>

scholarly journals Twitter Networks’ Centrality Measures of the Association of Health Journalist (ANIS): the Case of Vaccines - Introduction and Theoretical Framework

2020 ◽  
Vol 3 (2) ◽  
pp. 12
Author(s):  
Miguel Martín Cárdaba ◽  
Rafael Carrasco Polaino ◽  
Ubaldo Cuesta Cambra
Keyword(s):  
Social Networks ◽  
Public Opinion ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Theoretical Framework ◽  
Communication Strategy ◽  
Centrality Measures ◽  
The Social ◽  
One Year

The popularization of Internet and the rise of social networks have offered an unbeatable opportunity for anti-vaccines, especially active communicators, to spread their message more effectively causing a significant impact on public opinion. A great amount of research has been carried out to understand the behavior that anti-vaccine communities show on social networks. However, it seems equally relevant to study the behavior that communities and communicators “pro vaccines” perform in these networks. Therefore, the objective of this research has been to study how members of the Spanish Association of Health Journalist (ANIS) communicate and use the social network Twitter. More specifically, the different interactions made by ANIS partners were analyzed through the so-called “centrality measures of social network analysis” (SNA), to check the configuration of the user network and detect those most relevant by their indexes of centrality, intermediation or mentions received. The research monitored 142 twitter accounts for one year analyzing 254 twits and their 2.671 interactions. The research concluded that the network of ANIS partners on Twitter regarding vaccines has little cohesion and has several components not connected to each other, in addition to the fact that there are users outside the association that show greater relevance than the partners themselves. We also concluded that there are an important lack of planning and direction in the communication strategy of ANIS on Twitter, which limits the dissemination of important content.

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