Peer interaction and social network analysis of online communities with the support of awareness of different contexts

2015 ◽  
Vol 10 (2) ◽  
pp. 139-159 ◽  
Author(s):  
Jian-Wei Lin ◽  
Li-Jung Mai ◽  
Yung-Cheng Lai
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Online Communities ◽  
Peer Interaction

Using Social Network Analysis to Guide Theoretical Sampling in an Ethnographic Study of a Virtual Community

2011 ◽  
pp. 157-174 ◽  
Author(s):  
Enrique Murillo
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Online Communities ◽  
Online Community ◽  
Virtual Community ◽  
Ethnographic Study ◽  
Qualitative Studies ◽  
The Social ◽  
Theoretical Sampling

Social Network Analysis (SNA) provides a range of models particularly well suited for mapping bonds between participants in online communities and thus reveal prominent members or subgroups. This can yield valuable insights for selecting a theoretical sample of participants or participant interactions in qualitative studies of communities. This chapter describes a procedure for collecting data from Usenet newsgroups, deriving the social network created by participant interaction, and importing this relational data into SNA software, where various cohesion models can be applied. The technique is exemplified by performing a longitudinal core periphery analysis of a specific newsgroup, which identified core members and provided clear evidence of a stable online community. Discussions dominated by core members are identified next, to guide theoretical sampling of text-based interactions in an ongoing ethnography of the community.

Peer Assistance and Interaction in an Online Forum

2011 ◽  
pp. 118-130
Author(s):  
Ugur Kale
Keyword(s):  
Content Analysis ◽  
Instructional Design ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Peer Interaction ◽  
Graduate Level ◽  
Online Forum ◽  
Peer Assistance ◽  
To Receive

This study examines peer interaction and peer assistance observed in on an online forum, part of a graduate level instructional design course during the 2008 spring academic term. It incorporates both content analysis and social network analysis techniques. The content analysis results showed that the four types of peer assistance adopted from an existing framework were adequate to categorize the peer assistance that the students received during the study. Students tended to receive more Reflective assistance from their peers if their reading reflections provided high relevance to the course projects. Social network analysis results revealed that while 70% of the students provided peer assistance to one another, they were less likely to go beyond the course requirement of posting toward to end of the semester. Also, a further analysis demonstrated how SNA approach may help examine the influences of actor attributes on their observed communication.

scholarly journals Exploring Behavior of People with Suicidal Ideation in a Chinese Online Suicidal Community

2018 ◽  
Vol 16 (1) ◽  
pp. 54 ◽  
Author(s):  
Zheng Wang ◽  
Guang Yu ◽  
Xianyun Tian
Keyword(s):  
Social Media ◽  
Social Network ◽  
Social Network Analysis ◽  
Suicidal Ideation ◽  
Network Analysis ◽  
Online Communities ◽  
Chinese Women ◽  
Intervention Strategies ◽  
Effective Prevention ◽  
Social Media Platforms

People with suicidal ideation (PSI) are increasingly using social media to express suicidal feelings. Researchers have found that their internet-based communication may lead to the spread of suicidal ideation, which presents a set of challenges for suicide prevention. To develop effective prevention and intervention strategies that can be efficiently applied in online communities, we need to understand the behavior of PSI in internet-based communities. However, to date there have been no studies that specifically focus on the behavior of PSI in Chinese online communities. A total of 4489 postings in which users explicitly expressed their suicidal ideation were labeled from 560,000 postings in an internet-based suicidal community on Weibo (one of the biggest social media platforms in China) to explore their behavior. The results reveal that PSI are significantly more active than other users in the community. With the use of social network analysis, we also found that the more frequently users communicate with PSI, the more likely that users would become suicidal. In addition, Chinese women may be more likely to be at risk of suicide than men in the community. This study enriches our knowledge of PSI’s behavior in online communities, which may contribute to detecting and assisting PSI on social media.

scholarly journals Network Analysis of Political Internet Communities: from Formalized to «Unobserved» Groups

2021 ◽  
pp. 160-182
Author(s):  
Olga Popova ◽  
Sergey Suslov
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Online Communities ◽  
Latent Dirichlet Allocation ◽  
The Political ◽  
Analysis Methods ◽  
Methods And Techniques ◽  
Political Communities

The article is dedicated to the development of the political communities in social networks analysis methods. Main stages of network approach in the political science is described in the research. Researchers review the most significant methods and techniques in the political online communities studies for the last decade. The article shows the contemporary Russian scientists contribution in the development of online communities learning techniques. Networks and social network analysis methods and techniques become universal scientific approaches for several scientific fields. Boundary-transcending trends were critical means of science integration. Researchers present the results of experiment in which evaluate the possibilities of study unobserved political groups using latent Dirichlet allocation (LDA) model. The brief LDA foundation history and possible modifications for social topic modeling based on social networks data are discribed in the review. Using sample from one feed aggregator telegram channel in period of 2020 autumn, the authors display the most valuable topics in the Russian segment of political communication. Also it provides communities ideological preferences. Modified qualitative sociological methods can be used in online political communities discursive features research without any specific computer science techniques. Since about 70% of the Internet data are generated in the social networks, velocity and volume data necessitate new data mining techniques, databases capacity and computation processes. In other words, it provides a big data approach in social network analysis.

scholarly journals Detecting Communities in Science Blogs

2017 ◽  
Author(s):  
Christina Kirk Pikas
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Spin Glass ◽  
Community Detection ◽  
Online Communities ◽  
Subject Area ◽  
Analysis Methods ◽  
Science Blogs

Many scientists maintain blogs and participate in online communities through their blogs and other scientists' blogs. This study used social network analysis methods to locate and describe online communities in science blogs. The structure of the science blogosphere was examined using links between blogs in blogrolls and in comments. By blogroll, the blogs are densely connected and cohesive subgroups are not easily found. Using spin glass community detection, six cohesive subgroups loosely corresponding to subject area were found. By commenter links, the blogs form into more easily findable general subject area or interest clusters.

Exploring the Peer Interaction Effects on Learning Achievement in a Social Learning Platform Based on Social Network Analysis

2017 ◽  
Vol 15 (3) ◽  
pp. 65-85 ◽  
Author(s):  
Yu-Tzu Lin ◽  
Ming-Puu Chen ◽  
Chia-Hu Chang ◽  
Pu-Chen Chang
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Social Learning ◽  
Network Analysis ◽  
Peer Interaction ◽  
Peer Interactions ◽  
Learning Achievement ◽  
Learning Platform ◽  
The Social ◽  
College Course

The benefits of social learning have been recognized by existing research. To explore knowledge distribution in social learning and its effects on learning achievement, we developed a social learning platform and explored students' behaviors of peer interactions by the proposed algorithms based on social network analysis. An empirical study was also conducted on a college course to investigate the correlation between peer interaction and learning achievement. The experiment results show that the students who tended to actively contribute knowledge to peers on the social learning platform had better learning achievements than the students who were used to the passive reception of knowledge. Besides, the knowledge transmitters and intermediaries performed better in learning achievement as well, and the knowledge contributors had closer interactions with their peers. The implications derived from the findings can inspire instructors/researchers to facilitate effective social learning, and provide suggestions to develop effective algorithms to analyze social interaction behaviors.

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