scholarly journals Social Network Analysis and Churn Prediction in Telecommunications Using Graph Theory

Entropy ◽  
2020 ◽  
Vol 22 (7) ◽  
pp. 753 ◽  
Author(s):  
Stefan M. Kostić ◽  
Mirjana I. Simić ◽  
Miroljub V. Kostić
Keyword(s):  
Graph Theory ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Churn Prediction ◽  
Network Graph ◽  
Network Analytics ◽  
Telecommunications Market ◽  
Market Saturation ◽  
Important Nodes

Due to telecommunications market saturation, it is very important for telco operators to always have fresh insights into their customer’s dynamics. In that regard, social network analytics and its application with graph theory can be very useful. In this paper we analyze a social network that is represented by a large telco network graph and perform clustering of its nodes by studying a broad set of metrics, e.g., node in/out degree, first and second order influence, eigenvector, authority and hub values. This paper demonstrates that it is possible to identify some important nodes in our social network (graph) that are vital regarding churn prediction. We show that if such a node leaves a monitored telco operator, customers that frequently interact with that specific node will be more prone to leave the monitored telco operator network as well; thus, by analyzing existing churn and previous call patterns, we proactively predict new customers that will probably churn. The churn prediction results are quantified by using top decile lift metrics. The proposed method is general enough to be readily adopted in any field where homophilic or friendship connections can be assumed as a potential churn driver.

scholarly journals Group Measures and Modeling for Social Networks

2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
Vincent Levorato
Keyword(s):  
Complex System ◽  
Social Networks ◽  
Graph Theory ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Network Modeling ◽  
Complex Interactions ◽  
Social Network Modeling

Social network modeling is generally based on graph theory, which allows for study of dynamics and emerging phenomena. However, in terms of neighborhood, the graphs are not necessarily adapted to represent complex interactions, and the neighborhood of a group of vertices can be inferred from the neighborhoods of each vertex composing that group. In our study, we consider that a group has to be considered as a complex system where emerging phenomena can appear. In this paper, a formalism is proposed to resolve this problematic by modeling groups in social networks using pretopology as a generalization of the graph theory. After giving some definitions and examples of modeling, we show how some measures used in social network analysis (degree, betweenness, and closeness) can be also generalized to consider a group as a whole entity.

scholarly journals SOCIAL NETWORK ANALYSIS FOR CHURN PREDICTION IN TELECOM DATA

2016 ◽  
pp. 295-302
Author(s):  
PUSHPA PUSHPA ◽  
Dr. Shobha G
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Social World ◽  
Centrality Measures ◽  
Churn Prediction ◽  
Huge Amount ◽  
Analysis Techniques ◽  
Manual Analysis ◽  
The Social

Social Network Analysis (SNA) is a set of research procedures for identifying group of people who share common structures in systems based on the relations among actors. Grounded in graph and system theories, this approach has proven to be powerful measures for studying networks in various industries like Telecommunication, banking, physics and social world, including on the web. Since Telecommunication industries deals with huge amount of data, manual analysis of data is very difficult. In this paper we explore the Social Network Analysis techniques for Churn Prediction in Telecom data. Typical work on social network analysis includes the construction of multi-relational telecom social network and centrality measures for prediction of churners in telecom social network.

Emerging Forms of Collaboration

2016 ◽  
pp. 69-99
Author(s):  
Alexandra Antonopoulou ◽  
Eleanor Dare
Keyword(s):  
Graph Theory ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Community Of Practice ◽  
Motion Capture ◽  
Interaction Design ◽  
Collaborative Technologies ◽  
Custom Made ◽  
New Form

The chapter will outline the implications of two projects, namely the ‘Phi Books' (2008) and the ‘Digital Dreamhacker' (2011). These novel projects serve here as case studies for investigating new and challenging ways of advancing collaborative technologies, using in particular, Communities of Practice and insights gained from both embodiment and graph theory (social network analysis) as well as design. Both projects were developed collaboratively, between a computer programmer and a designer and a wider community of practice, consisting of other artists, writers, technologists and designers. The two systems that resulted also acted as methodologies, instigated by the authors with a view to facilitate, explore and comment on the act of collaboration. Both projects are multi-disciplinary, spanning ideas and techniques from mathematics and art, design and computer programming. The projects deploy custom-made software and fiction enmeshed structures, drawing upon methodologies that are embedded with dreams and stories while at the same time being informed by cutting-edge research into human behaviour and interaction design. The chapter will investigate how the projects deployed techniques and theoretical insights from social network analysis as well as motion capture technology and the wider concept of a Community of Practice, to extend and augment existing collaborative methods. The chapter draws upon Wenger et al (2002), as well as Siemens (2014) and Borgatti et al (2009), and will explore the idea of a new form of collective social and technological collaborative grammar, deploying gesture as well as Social Network Analysis. Moreover, the featured projects provide insights into the ways in which digital technology is changing society, and in turn, the important ways in which technology is embedded with the cultural and economic prerogatives of increasingly globalized cultures.

Structural Analysis With Graphs

2020 ◽  
pp. 31-47
Keyword(s):  
Social Networks ◽  
Graph Theory ◽  
Social Network ◽  
Social Network Analysis ◽  
Structural Analysis ◽  
Network Analysis ◽  
Social Research ◽  
Analysis Methods

Graphs are mathematical formalisms that represent social networks very well. Analysis methods using graph theory have started to develop substantially along with the advancement of mathematics and computer sciences in recent years, with contributions from several disciplines including social network analysis. Learning how to use graphs to represent social networks is important not only for employing theoretical insights of this advanced field in social research, but also for the practical purposes of utilizing its mature and abundant tools. This chapter explores structural analysis with graphs.

Abstract P214: Social Network Analysis of a Community Aphasia Group Pre- And Post-Covid: Implications for Future Planning

Stroke ◽  
2021 ◽  
Vol 52 (Suppl_1) ◽  
Author(s):  
Tom Sather ◽  
Anna Livera
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Time Frame ◽  
Directed Network ◽  
Negative Consequences ◽  
Network Graph ◽  
Future Planning ◽  
Network Characteristics ◽  
The Impact

Introduction: Among the many negative consequences of aphasia is an altered social network. Social network analysis supports an objective, quantitative evaluation of social networks among individuals with aphasia along with potential impacts of social programming and interventions on an individual’s social network. Social network analysis may also support better understanding of the impact of Covid on individuals with aphasia. Aims: This pilot evaluation utilized social network analysis via R to evaluate the social network characteristics of a community-based aphasia network across a 12-month pre-Covid period. Social network aphasia group data for a standard duration of time pre- and post-Covid were also compared to identify potential social implications of Covid in a population already at higher risk for reduced social interactions. This presentation will also provide fundamental concepts relevant to social network analysis for those interested in pursuing such analysis in further depth. Methods: Twelve months of pre-Covid aphasia group program attendance data were examined using the visNetwork R package. An additional six months of Covid-era time frame data were also analyzed.The primary relationship function of “ a attended b” (where a = individual participant and b = event/setting) was used in the analysis. Multiple social network characteristics were analyzed and displayed including node, edgeness, directionality, weight, and centrality indices across individuals with aphasia, care partners and community members and settings. Results and Conclusions: Network analysis reveals a directed network graph with primarily unidirectional relationships. There is an emergence of several aphasia group participant behavior types, both pre- and post-Covid, relevant for future planning including: communities of individuals who have similar behaviors in terms of type of event attendance; key individuals who are "heavy users" of various services in terms of frequency and breadth of event attendance; and peripheral users who use only one service. Post-Covid social network implications are discussed including supports to mitigate negative impacts of Covid on social network composition.

Sexual partners’ referral for HIV testing through social networking platforms: A social network analysis (Preprint)

2021 ◽  
Author(s):  
Piao-Yi Chiou ◽  
Chien-Ching Hung ◽  
Chien-Yu Chien
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Social Networking ◽  
Hiv Testing ◽  
Sexual Partners ◽  
Hiv Positive ◽  
Network Graph ◽  
Hiv Test ◽  
The Social

BACKGROUND Men who have sex with men (MSM) who undergo HIV voluntary counselling and testing (VCT) usually self-identify as having many sexual partners and as being exposed to risky sexual networks. Limited research discusses the application of motivative interviews and convenience referral platforms for MSM to facilitate the referral of sexual partners to HIV testing. The social network analysis (SNA) of such referral strategy remains unclear. OBJECTIVE To evaluate the effects of sexual partners’ referral through the social networking platforms for HIV testing and the test results after having elicited interviews with MSM, compare the different characteristics and risk behaviors of the subgroups, and to explore the unknown sexual affiliations through visualizing and quantifying the social network graph. METHODS This is a cohort study design. Purposeful sampling was used to recruit the index subjects at a community HIV screening station that is frequented by MSM in Taipei City on Friday and Saturday nights. Respondent-driven sampling was used to recruit the sexual partners. Partner-elicited interviews were conducted by trained staff before the VCT to motivate MSM to become the referrer to refer sexual partners via the Line application (app) or to disclose the account and profile on the relevant social networking platforms. The rapid HIV test was delivered to the referred sexual partners and the recruitment process continued in succession until leads were exhausted. RESULTS After the interviews, 28.2% (75/266) MSM were successfully persuaded to be index subjects in the first wave, referring 127 sexual partners via the Line app for the rapid HIV testing, and disclosing 40 sexual partners. The index subjects and the tested sexual partners exhibited higher numbers of sexual partners (F = 3.83, P = .023), higher frequencies of anal intercourse (F = 10.10, P < .001), and higher percentages of those who had not previously received HIV testing (x2 = 6.106, P = .047) when compared to the subjects without referrals. The newly HIV-seropositivity rate of tested sexual partners was 2.4%, which was higher than the other two groups. The SNA discovered four types of sexual affiliation, namely chain, Y, star, and complicated type. The complicated type had the most HIV-positive nodes. There were 26.87% (43/160) of the HIV-negative sexual partners who had sexual affiliations with HIV-positive nodes; 40% of them (10/25) were untested sexual partners, who had directly sexual affiliation with HIV-positive node. Four transmission bridge was found in the network graph. CONCLUSIONS Partner-elicited interviews can effectively promote the referral or disclosure sexual partners via social networking platforms for HIV testing and HIV case finding, and can reveal unknown sexual affiliations of MSM that can facilitate the development of a tailored prevention program.

scholarly journals Who Is the Keyman? Integrating Two-Stage DEA and Social Network Analysis to Evaluate Operational and Environmental Efficiency in the Semiconductor Industry

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Tzu-Yi Fang
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Semiconductor Industry ◽  
Operational Efficiency ◽  
Environmental Efficiency ◽  
Decision Makers ◽  
Network Graph ◽  
Two Stage ◽  
A Company

The study considers the semiconductor industry’s business process to be made up of two stages. In the business development process, a company generates profit and consumes energy while polluting the environment. After the two-stage data envelopment analysis approach was employed for calculating the operational efficiency and environmental efficiency, social network analysis was used to compare the manner in which the internal advantages or individual process factors of 28 semiconductor companies contribute to efficiency. A network graph was plotted to visualize relationships, with each node in the network graph representing a company. This graph was plotted to help decision-makers and manufacturers understand information communication among companies and the importance of the company in the network and help companies develop a mutual understanding to improve operational efficiency. The results of the study indicated that having an efficient company does not necessarily mean that the company plays a key role in the entire industry. The results provide decision-makers with references for improvements and information for learning from these references.

Computing secure sets in graphs using answer set programming

2015 ◽  
Vol 30 (4) ◽  
pp. 837-862 ◽  
Author(s):  
Michael Abseher ◽  
Bernhard Bliem ◽  
Günther Charwat ◽  
Frederico Dusberger ◽  
Stefan Woltran
Keyword(s):  
Graph Theory ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Answer Set Programming ◽  
Np Hard ◽  
Weighted Graphs ◽  
Answer Set

Abstract The notion of secure sets is a rather new concept in the area of graph theory. Applied to social network analysis, the goal is to identify groups of entities that can repel any attack or influence from the outside. In this article, we tackle this problem by utilizing Answer Set Programming (ASP). It is known that verifying whether a set is secure in a graph is already co-NP-hard. Therefore, the problem of enumerating all secure sets is challenging for ASP and its systems. In particular, encodings for this problem seem to require disjunction and also recursive aggregates. Here, we provide such encodings and analyse their performance using the Clingo system. Furthermore, we study several problem variants, including multiple secure or insecure sets, and weighted graphs.

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