Experimental Analysis of Keyword-based Social Network Similarity Approach for Document Classification

2020 ◽  
Author(s):  
Furkan Goz ◽  
Osman Kabasakal ◽  
Alev Mutlu
Keyword(s):  
Social Network ◽  
Experimental Analysis ◽  
Document Classification ◽  
Network Similarity

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.

scholarly journals Social network characteristics and alcohol use by ethnic origin: An ego-based network study on peer similarity, social relationships, and co-existing drinking habits among young Swedes

PLoS ONE ◽  
2021 ◽  
Vol 16 (4) ◽  
pp. e0249120
Author(s):  
Nina-Katri Gustafsson ◽  
Jens Rydgren ◽  
Mikael Rostila ◽  
Alexander Miething
Keyword(s):  
Social Network ◽  
Alcohol Use ◽  
Ethnic Origin ◽  
Network Characteristics ◽  
Closed Networks ◽  
Drinking Habits ◽  
Cultural Aspects ◽  
Sex Risk ◽  
Network Similarity ◽  
Demographic Similarity

The study explores how social network determinants relate to the prevalence and frequency of alcohol use among peer dyads. It is studied how similar alcohol habits co-exist among persons (egos) and their peers (alters) when socio-demographic similarity (e.g., in ethnic origin), network composition and other socio-cultural aspects were considered. Data was ego-based responses derived from a Swedish national survey with a cohort of 23-year olds. The analytical sample included 7987 ego-alter pairs, which corresponds to 2071 individuals (egos). A so-called dyadic design was applied i.e., all components of the analysis refer to ego-alter pairs (dyads). Multilevel multinomial-models were used to analyse similarity in alcohol habits in relation to ego-alter similarity in ethnic background, religious beliefs, age, sex, risk-taking, educational level, closure in network, duration, and type of relationship, as well as interactions between ethnicity and central network characteristics. Ego-alter similarity in terms of ethnic origin, age and sex was associated with ego-alter similarity in alcohol use. That both ego and alters were non-religious and were members of closed networks also had an impact on similarity in alcohol habits. It was concluded that network similarity might be an explanation for the co-existence of alcohol use among members of peer networks.

scholarly journals Social network characteristics and alcohol use among young Swedes with different ethnic backgrounds

2019 ◽  
Vol 29 (Supplement_4) ◽  
Author(s):  
A Miething ◽  
N K Gustafsson ◽  
M Rostila ◽  
J Rydgren
Keyword(s):  
Social Network ◽  
Alcohol Use ◽  
Binge Drinking ◽  
Market Integration ◽  
Ethnic Background ◽  
Outcome Variable ◽  
Network Characteristics ◽  
Cultural Aspects ◽  
Network Similarity ◽  
Network Composition

Abstract Background The study explores how social network determinants relate to the prevalence and frequency of alcohol use of members of social networks. In a so-called dyadic design we study how similar alcohol habits co-exist among individuals (egos) and their peers (alters), when variables such as ethnic background, network composition, and other socio-cultural aspects are considered. Methods The data were derived from a Swedish survey entitled “Social Capital and Labor Market Integration: A Cohort Study.” The study participants (egos; n = 1989) were around age 23 at the time of the interview. A so-called dyadic design was applied, which means that all components of the analysis refer to ego-alter pairs (n = 7828). The outcome variable considered how alcohol prevalence and frequency of binge-drinking co-exist between egos and their alters. The independent variables also measured mutual attributes and behaviors - whether egos and alters were at the same age and sex, had same ethnic background, were relatives or friends, had similar religious affiliations, or intensely interacted with friends. Results The analysis revealed that ego-alter similarity in terms of age, sex and ethnic background predict ego-alter similarity in alcohol use and binge-drinking. For example, if egos and alters shared a similar ethnic background, their risk of alcohol use was at least 30 percent higher as compared to those with different ethnic backgrounds. Relative to ego-alter pairs with mixed ethnic backgrounds, the odds of binge-drinking were highest for ego-alters pairs with Yugoslavian background (OR 1.76; 95% CI 1.27-2.42), followed by those with Iranian (OR 1.57; 1.04-2.35) and Swedish background (OR 1.28; 0.84-1.95). Conclusions We conclude that network similarity (i.e., homophily) is an important explanation for the co-existence of alcohol use among members of peer networks. Alcohol use is more common in homogeneous peer dyads representing population groups with higher use. Key messages Peer similarity predicts alcohol use and binge drinking. Ethnic similarity of peers is associated with increased alcohol use and binge drinking.

The social network

2013 ◽  
Vol 44 (2) ◽  
pp. 22
Author(s):  
ALAN ROCKOFF
Keyword(s):  
Social Network ◽  
The Social

Abstract #1249: Novel Use of Physician Social Network Data to Map the Gap in the Endocrinology Workforce

2015 ◽  
Vol 21 ◽  
pp. 301
Author(s):  
Armand Krikorian ◽  
Lily Peng ◽  
Zubair Ilyas ◽  
Joumana Chaiban
Keyword(s):  
Social Network ◽  
Network Data ◽  
Social Network Data

Correlating Personality and Actual Phone Usage

2014 ◽  
Vol 35 (3) ◽  
pp. 158-165 ◽  
Author(s):  
Christian Montag ◽  
Konrad Błaszkiewicz ◽  
Bernd Lachmann ◽  
Ionut Andone ◽  
Rayna Sariyska ◽  
...  
Keyword(s):  
Big Data ◽  
Social Network ◽  
Mobile Phone ◽  
Mobile Phones ◽  
Self Report ◽  
Psychological Variables ◽  
New Approach ◽  
Report Data ◽  
Self Report Data ◽  
Voice Calls

In the present study we link self-report-data on personality to behavior recorded on the mobile phone. This new approach from Psychoinformatics collects data from humans in everyday life. It demonstrates the fruitful collaboration between psychology and computer science, combining Big Data with psychological variables. Given the large number of variables, which can be tracked on a smartphone, the present study focuses on the traditional features of mobile phones – namely incoming and outgoing calls and SMS. We observed N = 49 participants with respect to the telephone/SMS usage via our custom developed mobile phone app for 5 weeks. Extraversion was positively associated with nearly all related telephone call variables. In particular, Extraverts directly reach out to their social network via voice calls.

Extraverts Have Larger Social Network Layers

2011 ◽  
Vol 32 (3) ◽  
pp. 161-169 ◽  
Author(s):  
Thomas V. Pollet ◽  
Sam G. B. Roberts ◽  
Robin I. M. Dunbar
Keyword(s):  
Social Network ◽  
Social Relationships ◽  
Outer Layer ◽  
Network Size ◽  
Emotional Intensity ◽  
Emotional Closeness ◽  
Network Layer ◽  
Network Layers ◽  
Social Network Size

Previous studies showed that extraversion influences social network size. However, it is unclear how extraversion affects the size of different layers of the network, and how extraversion relates to the emotional intensity of social relationships. We examined the relationships between extraversion, network size, and emotional closeness for 117 individuals. The results demonstrated that extraverts had larger networks at every layer (support clique, sympathy group, outer layer). The results were robust and were not attributable to potential confounds such as sex, though they were modest in size (raw correlations between extraversion and size of network layer, .20 < r < .23). However, extraverts were not emotionally closer to individuals in their network, even after controlling for network size. These results highlight the importance of considering not just social network size in relation to personality, but also the quality of relationships with network members.

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