scholarly journals Mobilizing homeless youth for HIV prevention: a social network analysis of the acceptability of a face-to-face and online social networking intervention

2012 ◽  
Vol 27 (2) ◽  
pp. 226-236 ◽  
Author(s):  
E. Rice ◽  
E. Tulbert ◽  
J. Cederbaum ◽  
A. Barman Adhikari ◽  
N. G. Milburn
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Hiv Prevention ◽  
Social Networking ◽  
Homeless Youth ◽  
Online Social Networking ◽  
Face To Face

Applications of Data Mining in Dynamic Social Network Analysis

2013 ◽  
pp. 110-121
Author(s):  
Manish Kumar
Keyword(s):  
Data Mining ◽  
Social Networks ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Social Networking ◽  
Knowledge Discovery ◽  
Online Social Networking ◽  
Dynamic Social Network ◽  
Business Goals

Social Networks are nodes consisting of people, groups and organizations growing dynamically. The growth is horizontal as well as vertical in terms of size and number. Social network analysis has gained success due to online social networking and sharing sites. The accessibility of online social sites such as MySpace, Facebook, Twitter, Hi5, Friendster, SkyRock and Beb offer sharing and maintaining large amount of different data. Social network analysis is focused on mining such data i.e. generating pattern of people’s interaction. The analysis involves the knowledge discovery that helps the sites as well as users in terms of usage and business goals respectively. Further it is desired that the process must be privacy preserving. This chapter describes the various mining techniques applicable on social networks data.

scholarly journals Strengths and weaknesses of the Net-Map tool for participatory social network analysis in resource management: Experience from case studies conducted on four continents

2018 ◽  
Vol 11 (2) ◽  
pp. 205979911878775 ◽  
Author(s):  
Barbara Schröter ◽  
Claudia Sattler ◽  
Frieder Graef ◽  
Cheng Chen ◽  
Estephania Delgadillo ◽  
...  
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Face To Face ◽  
Directed Information ◽  
Management Experience ◽  
Participatory Network ◽  
Network Mapping ◽  
Depth Interviews

For researchers, conducting face-to-face interviews is always a challenge as it often turns into a one-way directed information retrieval. Therefore, interviewees not always are very motivated, enthusiastic and cooperative in responding to the questions. In the end, this has implications for the quality of the interview data. To improve the interview setting and the resulting data, in several projects the Net-Map tool was used to conduct participatory social network analysis. The tool is a combination of in-depth interviews and participatory network mapping. During the interviews, the interviewee draws the network of relevant actors, notes down their motivations and evaluates and displays the actors’ influence and benefits by building towers using any kind of stacks. In this research note, we present the strengths and weaknesses of the method against the experiences with applying the Net-Map tool on four different continents and give ideas for improvements and further research.

scholarly journals Social Network Analysis to Examine Interaction Patterns in Knowledge Building Communities

2010 ◽  
Vol 36 (1) ◽  
Author(s):  
Donald N. Philip
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Knowledge Building ◽  
Group Processes ◽  
Interaction Patterns ◽  
Face To Face ◽  
Grade 5 ◽  
Teachers And Students ◽  
Building Community

This paper describes use of social network analysis to examine student interaction patterns in a Grade 5/6 Knowledge Building class. The analysis included face-to-face interactions and interactions in the Knowledge Forum® Knowledge Building environment. It is argued that sociogram data are useful to reveal group processes; in sociological terms, the community lies in the connections among the group. A classroom of unconnected individuals is unlikely to form as a Knowledge Building community; data analyses reported in this study show promise in understanding the dynamics of Knowledge Building in a consistent and measurable way. The strength of the work is not in particular patterns demonstrated but in new forms of assessment and their potential to inform work as it proceeds. The research reported shows that teachers and students are finding social network analysis useful and that through their engagement research-practitioner-engineer teams are better positioned to develop tools to advance Knowledge Building pedagogy.

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 Brand influence online: cross-platform social network analysis on the enablement of effective brand communities

2021 ◽  
Author(s):  
Cameron Munro
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Social Networking ◽  
Methodological Approach ◽  
Brand Community ◽  
Brand Communities ◽  
Online Brand Community ◽  
Network Properties ◽  
Cross Platform

This paper aims to provide a systematic methodological approach for online brand community assessment across multiple social networking platforms. Analysis of influential brands was conducted utilizing a social network analysis (SNA) perspective. Brand communities were scored based on network properties and content analysis. Background research provided a framework of recommended community enablement strategies to determine what type of content and approach is most conducive to brand community proliferation. Based on network analysis and on congruency of following academically suggested community enablement triggers and behavioural dimensions, it was determined that the most effective brand at enabling community across all platforms within the study was Yeti Coolers. Instagram was the focal platform providing engaging content to be shared across networks

Social Networks in Information Systems

2010 ◽  
pp. 392-410 ◽  
Author(s):  
Hernâni Borges de Freitas ◽  
Alexandre Barão ◽  
Alberto Rodrigues da Silva
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Information Systems ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Social Networking ◽  
Information Exchange ◽  
Group Processes ◽  
Communication Tools ◽  
Social Entities

A social network represents a set of social entities that interact through relationships like friendship, co-working, or information exchange. Social Network Analysis studies the patterns of relationships among social entities and can be used to understand and improve group processes. The arrival of new communication tools and networking platforms, especially the Web 2.0 Social Networking Services, opened new opportunities to explore the power of social networks inside and outside organizations. This chapter surveys the basic concepts of social networks methods, approaches, tools, and services. In particular, this chapter analyzes state-of-the-art social networks, explaining how useful Social Network Analysis can be in different contexts and how social networks can be represented, extracted, and analyzed in information systems.

scholarly journals Social Network Analysis of Intensive Care Unit Health Care Professionals Measured by Wearable Sociometric Badges: Longitudinal Observational Study (Preprint)

2020 ◽  
Author(s):  
Eiji Kawamoto ◽  
Asami Ito-Masui ◽  
Ryo Esumi ◽  
Mami Ito ◽  
Noriko Mizutani ◽  
...  
Keyword(s):  
Health Care ◽  
Intensive Care Unit ◽  
Intensive Care ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Health Care Professionals ◽  
Wearable Sensors ◽  
Interaction Data ◽  
Face To Face

BACKGROUND Use of wearable sensor technology for studying human teamwork behavior is expected to generate a better understanding of the interprofessional interactions between health care professionals. OBJECTIVE We used wearable sociometric sensor badges to study how intensive care unit (ICU) health care professionals interact and are socially connected. METHODS We studied the face-to-face interaction data of 76 healthcare professionals in the ICU at Mie University Hospital collected over 4 weeks via wearable sensors. RESULTS We detail the spatiotemporal distributions of staff members’ inter- and intraprofessional active face-to-face interactions, thereby generating a comprehensive visualization of who met whom, when, where, and for how long in the ICU. Social network analysis of these active interactions, concomitant with centrality measurements, revealed that nurses constitute the core members of the network, while doctors remain in the periphery. CONCLUSIONS Our social network analysis using the comprehensive ICU interaction data obtained by wearable sensors has revealed the leading roles played by nurses within the professional communication network.

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.

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