“The Company You Keep”: Unpacking a Measurement Model of Social Network Interdependence

2018 ◽  
Vol 13 (1) ◽  
pp. 19-25 ◽  
Author(s):  
James Stein
Keyword(s):  
Social Network ◽  
Measurement Model ◽  
Network Interdependence

scholarly journals A Measurement Model of Mutual Influence for Information Dissemination

Entropy ◽  
2020 ◽  
Vol 22 (7) ◽  
pp. 725
Author(s):  
Liang Zhang ◽  
Yong Quan ◽  
Bin Zhou ◽  
Yan Jia ◽  
Liqun Gao
Keyword(s):  
Social Network ◽  
Information Dissemination ◽  
Mutual Influence ◽  
Synthetic Data ◽  
Measurement Model ◽  
Mobile Internet ◽  
Information Propagation ◽  
Information Cascade ◽  
Data Set ◽  
Access Information

The recent development of the mobile Internet and the rise of social media have significantly enriched the way people access information. Accurate modeling of the probability of information propagation between users is essential for studying information dissemination issues in social networks. As the dissemination of information is inseparable from the interactions between users, the probability of propagation can be characterized by such interactions. In general, there are differences in the dissemination modes of information that carry different topics in a real social network. Using these factors, we propose a method (TMIVM) to measure the mutual influence between users at the topic level. The method associates two vectorization parameters for each user—an influence vector and a susceptibility vector—where the dimensions of the vector represent different topic categories. The magnitude of the mutual influence between users on different topics can be obtained by the product of the corresponding elements of the vectors. Specifically, in this article, we fit a social network historical information cascade data through Survival Analysis to learn the parameters of the influence and susceptibility vectors. The experimental results on a synthetic data set and a real Microblog data set show that this method better measures the propagation probability and information cascade predictions compared to other methods.

Quality of Regional Election Implementation as Determinant of Performance of Simultaneous Regional Election: Community Trust and Satisfaction as Mediation, and Regulatory Harmonization as Moderation

2021 ◽  
Vol 24 (01) ◽  
pp. 2150008
Author(s):  
Lely Indah Mindarti ◽  
Akmal Malik ◽  
Bambang Supriyono ◽  
Hermawan
Keyword(s):  
Social Network ◽  
Public Administration ◽  
Structural Equation ◽  
Measurement Model ◽  
Equation Model ◽  
Synchronous Communication ◽  
Community Trust ◽  
Regional Elections ◽  
The Impact

The objectives of this research are to analyze how to build the political and managerial balance of government in direct and simultaneous regional elections in Indonesia based on the managerial approach of government and the decentralization approach quantitatively. Data analysis uses the Social Network Analysis (SNA) or Social Network Theory (SNT) approach to map policies using the XL Node and first-order confirmatory factor analysis which is a form of measurement model in the Structural Equation Model (SEM). The population in this study is the Regency/City and Province Organizers of the 2018 elections, which are 88 pairs of Regional Heads/Deputy Regional Heads. The sample of this study was voters who assessed the quality of the elections and other variables, totaling 340 respondents. The results of the study indicate that community trust and community satisfaction can be mediation for the quality of the implementation of regional election to influence the performance of simultaneous regional election. In addition, harmonization of regulations is a moderating variable that can affect the quality of the implementation of regional elections, public trust, and public satisfaction with the performance of simultaneous regional elections. This study conducted a quantification study related to new approaches in building a balance with the managerial approach of governance (Rosenbloom, DH (2015). Public Administration: Understanding Management, Politics, and Law in the Public Sector, 8th ed. Boston, MA: McGraw-Hill; Frederickson, HG (1980). New Public Administration. University of Alabama Press; Frederickson, GN and NA Lynch (1984). The impact of synchronous communication on the problem of electing a leader in a ring. In Proc. 16th Annual ACM Symp. Theory of Computing, Washington, D.C., pp. 493–503. https://doi.org/10.1145/800057.808719 ) and the decentralization approach (Smith, BC (1985). Decentralization: The Territorial Dimension of the State. Taylor & Francis; Smith, BC (2012). Desentralisasi, Dimensi Teritorial Suatu Negara (diterjemahkan oleh Tim MIPI). Jakarta: MIPI).

The effect of intrinsic and extrinsic motivations on mobile coupon sharing in social network sites

2016 ◽  
Vol 26 (1) ◽  
pp. 101-119 ◽  
Author(s):  
Qing Tang ◽  
Xuefeng Zhao ◽  
Shan Liu
Keyword(s):  
Social Network ◽  
Sense Of Self ◽  
Social Network Sites ◽  
Measurement Model ◽  
Content Type ◽  
Positive Effects ◽  
Self Worth ◽  
Relationship Of ◽  
The Impact ◽  
The Relationship

Purpose – The purpose of this paper is to investigate the influence of two intrinsic (i.e. sense of self-worth and socializing) and two extrinsic motivations (i.e. economic reward and reciprocity) on mobile coupon (m-coupon) sharing by users in social network sites (SNSs). Moreover, this study examines how coupon proneness moderates the relationship between motivations and m-coupon sharing in SNSs. Design/methodology/approach – A research model that integrates four motivations, coupon proneness, and m-coupon sharing is developed. Quantitative data from 247 users are collected via online and offline survey. Partial least squares technique is employed to evaluate the measurement model, and hypotheses are tested through hierarchical regression analysis. Findings – Sense of self-worth, socializing, economic reward and reciprocity have positive effects on m-coupon sharing in SNSs. Furthermore, coupon proneness positively moderates the relationship of socializing and reciprocity with m-coupon sharing, whereas the moderating effects of coupon proneness on the relationship of sense of self-worth and economic reward with m-coupon sharing are insignificant. Originality/value – The findings highlight the integrated effects of coupon proneness and motivations on m-coupon sharing in SNS. The impact of socializing and reciprocity on m-coupon sharing is higher for users with higher coupon proneness. However, the effect of sense of self-worth and economic reward on m-coupon sharing is the same regardless of coupon proneness of users. Therefore, although users with different motivations should be identified, SNSs and merchants should develop different incentive mechanisms to promote m-coupon sharing among various users.

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

Instrumental and Ideological Union Commitment: Longitudinal Assessment of Construct Validity

2001 ◽  
Vol 17 (2) ◽  
pp. 98-111 ◽  
Author(s):  
Anders Sjöberg ◽  
Magnus Sverke
Keyword(s):  
Construct Validity ◽  
Temporal Stability ◽  
Strong Support ◽  
Internal Consistency Reliability ◽  
Measurement Model ◽  
Two Dimensions ◽  
Model Parameters ◽  
Longitudinal Assessment ◽  
Union Commitment ◽  
Union Participation

Summary: Previous research has identified instrumentality and ideology as important aspects of member attachment to labor unions. The present study evaluated the construct validity of a scale designed to reflect the two dimensions of instrumental and ideological union commitment using a sample of 1170 Swedish blue-collar union members. Longitudinal data were used to test seven propositions referring to the dimensionality, internal consistency reliability, and temporal stability of the scale as well as postulated group differences in union participation to which the scale should be sensitive. Support for the hypothesized factor structure of the scale and for adequate reliabilities of the dimensions was obtained and was also replicated 18 months later. Tests for equality of measurement model parameters and test-retest correlations indicated support for the temporal stability of the scale. In addition, the results were consistent with most of the predicted differences between groups characterized by different patterns of change/stability in union participation status. The study provides strong support for the construct validity of the scale and indicates that it can be used in future theory testing on instrumental and ideological union commitment.

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.

The Multilevel p2 Model

Methodology ◽  
2006 ◽  
Vol 2 (1) ◽  
pp. 42-47 ◽  
Author(s):  
Bonne J. H. Zijlstra ◽  
Marijtje A. J. van Duijn ◽  
Tom A. B. Snijders
Keyword(s):  
Social Network ◽  
Network Data ◽  
Mcmc Algorithm ◽  
Independent Observation ◽  
Single Observation ◽  
Multiple Networks ◽  
Social Network Data ◽  
Multiple Observations ◽  
Practical Support ◽  
The Social

The p 2 model is a random effects model with covariates for the analysis of binary directed social network data coming from a single observation of a social network. Here, a multilevel variant of the p 2 model is proposed for the case of multiple observations of social networks, for example, in a sample of schools. The multilevel p 2 model defines an identical p 2 model for each independent observation of the social network, where parameters are allowed to vary across the multiple networks. The multilevel p 2 model is estimated with a Bayesian Markov Chain Monte Carlo (MCMC) algorithm that was implemented in free software for the statistical analysis of complete social network data, called StOCNET. The new model is illustrated with a study on the received practical support by Dutch high school pupils of different ethnic backgrounds.

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