Session analysis of people search within a professional social network

2013 ◽  
Vol 64 (5) ◽  
pp. 929-950 ◽  
Author(s):  
Ru He ◽  
Jiong Wang ◽  
Jin Tian ◽  
Cheng-Tao Chu ◽  
Bradley Mauney ◽  
...  
Keyword(s):  
Social Network ◽  
Session Analysis ◽  
People Search

Productivity of Emerging Word Combinations in Toddlers With Specific Expressive Language Impairment

1997 ◽  
Vol 6 (4) ◽  
pp. 34-47 ◽  
Author(s):  
Steven H. Long ◽  
Lesley B. Olswang ◽  
Julianne Brian ◽  
Philip S. Dale
Keyword(s):  
Data Collection ◽  
Young Children ◽  
Language Impairment ◽  
Treatment Approach ◽  
Expressive Language ◽  
Semantic Consistency ◽  
Session Analysis

This study investigated whether young children with specific expressive language impairment (SELI) learn to combine words according to general positional rules or specific, grammatic relation rules. The language of 20 children with SELI (4 females, 16 males, mean age of 33 months, mean MLU of 1.34) was sampled weekly for 9 weeks. Sixteen of these children also received treatment for two-word combinations (agent+action or possessor+possession). Two different metrics were used to determine the productivity of combinatorial utterances. One metric assessed productivity based on positional consistency alone; another assessed productivity based on positional and semantic consistency. Data were analyzed session-by-session as well as cumulatively. The results suggest that these children learned to combine words according to grammatic relation rules. Results of the session-by-session analysis were less informative than those of the cumulative analysis. For children with SELI ready to make the transition to multiword utterances, these findings support a cumulative method of data collection and a treatment approach that targets specific grammatic relation rules rather than general word combinations.

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.

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.

Learning Conversation and Shared Network Leadership

2010 ◽  
Vol 9 (4) ◽  
pp. 181-194 ◽  
Author(s):  
Jürgen Weibler ◽  
Sigrid Rohn-Endres
Keyword(s):  
Qualitative Research ◽  
Grounded Theory ◽  
Social Network ◽  
Interorganizational Networks ◽  
Original Network ◽  
High Quality ◽  
Qualitative Research Design ◽  
Collective Processes ◽  
Shared Network ◽  
Practical Implications

This paper develops an understanding of how shared leadership emerges in social network interactions. On the basis of a qualitative research design (grounded theory methodology – GTM) our study in two interorganizational networks offers insights into the interplay between structures, individuals, and the collective for the emergence of shared network leadership (SNL). The network-specific Gestalt of SNL appears as a pattern of collective and individual leadership activities unified under the roof of a highly developed learning conversation. More importantly, our findings support the idea that individual network leadership would not emerge without embeddedness in certain high-quality collective processes of relating and dialogue. Both theoretical and practical implications of this original network leadership perspective are discussed.

Social network relationships as sources of maternal support and well-being.

1986 ◽  
Vol 22 (3) ◽  
pp. 310-316 ◽  
Author(s):  
Mary J. Levitt ◽  
Ruth A. Weber ◽  
M. Cherie Clark
Keyword(s):  
Social Network ◽  
Well Being ◽  
Maternal Support
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