Exploring the Relationship Between Social Interaction, Cognitive Processing and Learning Achievements in a MOOC Discussion Forum

2021 ◽  
pp. 073563312110273
Author(s):  
Zhi Liu ◽  
Ning Zhang ◽  
Xian Peng ◽  
Sannyuya Liu ◽  
Zongkai Yang ◽  
...  
Keyword(s):  
Social Network ◽  
Social Interaction ◽  
Network Analysis ◽  
Cognitive Processing ◽  
Learning Analytics ◽  
Discussion Forum ◽  
Community Type ◽  
Eigenvector Centrality ◽  
Community Types ◽  
The Relationship

In the field of learning analytics, mining the regularities of social interaction and cognitive processing have drawn increasing attention. Nevertheless, in MOOCs, there is a lack of investigations on the combination of social and cognitive behavioral patterns. To fill in this gap, this study aimed to uncover the relationship between social interaction, cognitive processing, and learning achievements in a MOOC discussion forum. Specifically, we collected the 3925 participants’ forum data throughout 16 weeks. Social network analysis and epistemic network analysis were jointly adopted to investigate differences in social interaction, cognitive processing between two achievement groups, and the differences in cognitive processing networks between two types of communities. Finally, moderation analysis was employed to examine the moderating effect of community types between cognitive processing and learning achievements. Results indicated that: (1) the high- and low-achieving groups presented significant differences in terms of degree, betweenness, and eigenvector centrality; (2) the stronger cognitive connections were found within the high-achieving group and the instructor-led community; (3) the cognitive processing indicators including insight, discrepancy, and tentative were significantly negative predictors of learning achievements, whereas inhibition and exclusive were significantly positive predictors; (4) the community type moderated the relationship between cognitive processing and learning achievements.

scholarly journals Central Actor Identification of Crime Group using Semantic Social Network Analysis

2019 ◽  
Vol 2 (1) ◽  
pp. 24
Author(s):  
Sylvert Prian Tahalea ◽  
Azhari SN
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Social Protection ◽  
Social Relation ◽  
Centrality Measures ◽  
Eigenvector Centrality ◽  
Criminal Cases ◽  
Central Actor ◽  
The Relationship

The Police as law enforcers who authorize in terms of social protection are expected to do both the prevention and investigation efforts also the settlement of criminal cases that occurred in the society. This research can help police to identify the main actor faster and leads to solving crime-cases. The use of overall centrality is very helpful in determining the main actors from other centrality measures. The purpose of this research is to identify the central actor of crimes done by several people. Semantic Social Network Analysis is used to perform central actor identification using five centrality measurements, such as degree centrality, betweenness centrality, closeness centrality, eigenvector centrality, and overall centrality. As for the relationship between actors, this research used social relation such as friendship, colleague, family, date or lover, and acquaintances. The relationship between actors is measured by first four centrality measures then accumulated by overall centrality to determine the main actor. The result showed 80.39% accuracy from 102 criminal cases collected with at least 3 actors involved in each case.

scholarly journals FACTORS AFFECTING DISPOSITION EFFECT IN EQUITY INVESTMENT: A SOCIAL NETWORK ANALYSIS APPROACH

2020 ◽  
Vol 5 (3) ◽  
pp. 64-86
Author(s):  
K. Kajol ◽  
Prasita Biswas ◽  
Ranjit Singh ◽  
Sana Moid ◽  
Amit Kumar Das
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Stock Market ◽  
Influencing Factors ◽  
Social Trust ◽  
Complete Analysis ◽  
Disposition Effect ◽  
Factors Affecting ◽  
The Relationship

The study aims at identifying the factors influencing the disposition effect acting on equity investors and further identifying the relationship between the influencing factors. The study aims at conducting a complete analysis of the influencing factors along with measuring their impact on disposition effect using Social Network Analysis (SNA).The factors affecting disposition effect on investors were identified through the literature review. Experts’ opinions were sought for determining the relationship among the factors and finally, the importance of those factors was analyzed using Social Network Analysis (SNA). It was found that social trust, investor emotion are the two most important factors affecting the other factors of disposition effect and consequently disposition effect finally. Besides, mental accounting; regret aversion, trading intensity, trading volume, and portfolio performance strongly influence the effect of disposition on investors because of their higher in-degree and out-degree. Therefore, the policymakers need to impart training to the investors to understand the mechanism of the stock market so that they can evaluate their standing in the stock market which, in the long run, will be reflected in their investment behavior. 

scholarly journals Homophily and Social Capital in a Network of Religious Congregations

Religions ◽  
2021 ◽  
Vol 12 (8) ◽  
pp. 653
Author(s):  
Jennifer M. McClure
Keyword(s):  
United States ◽  
Social Capital ◽  
Social Network ◽  
Network Analysis ◽  
Southeastern United States ◽  
Sociology Of Religion ◽  
Religious Congregations ◽  
Major Metropolitan Area ◽  
Curvilinear Relationships ◽  
The Relationship

This article investigates the relationship between homophily, the tendency for relationships to be more common among similar actors, and social capital in a social network of religious congregations from eight counties encompassing and surrounding a major metropolitan area in the southeastern United States. This network is inter-congregational, consisting of congregations and the relationships between them. Two types of social capital are investigated: the first involves the extent to which congregations bridge across structural holes, or bridge together otherwise disconnected congregations within the network; secondly, network closure involves the extent to which congregations are embedded in tight-knit clusters. Analyses use two types of homophily (religious and racial) to predict both outcomes, and they test linear and curvilinear relationships between both forms of homophily and the outcomes. Results indicate that congregations with moderate levels of religious homophily are more likely to bridge between otherwise disconnected congregations; however, congregations with low or high religious homophily as well as congregations with high racial homophily are more likely to be embedded in tight-knit relational clusters. This article contributes additional social network research on congregations and evidence of curvilinear relationships between homophily and social capital to the fields of social network analysis and sociology of religion.

scholarly journals Ego-Centric Social Network Analysis in Marketing of Fish From Cage Culture System In Simalungun District, Indonesia

2019 ◽  
Vol 8 (4) ◽  
pp. 105-113
Author(s):  
Feriel Amelia Sembiring ◽  
Fikarwin Zuska ◽  
Bengkel Ginting ◽  
Rizabuana Ismail ◽  
Henry Sitorus
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Network Analysis ◽  
Culture System ◽  
Qualitative Approach ◽  
Mutual Trust ◽  
Cage Culture ◽  
The Social ◽  
The Village ◽  
The Relationship

Aquaculture of Cage Culture is one of the main activities carried out by the community in the village of Haranggaol to fulfill their economic needs. This cultivation business establishes a relationship between traders and cages in terms of marketing their crops. There are 3 egocentric actors in the Haranggaol area. They are collectors (entrepreneurs/farmers who own capital), namely the Rohakinian group, the Siharo group, and the Paimaham group. Through these three egocentric actors, a social network is formed with several alters. Based on the qualitative approach with use Ucinet software, the mapping of their social networks can be seen as follows: alter actors connected to the Rohakinian group are 12 farmers in the group and 2 farmers outside the group with a density of 0.033. There are 27 alter actors connected to the Siharo group, 21 from the group and 6 from outside the group with a density of 0.014. There are 27 alter actors connected to the Paimaham group, namely 36 farmers from their groups and 10 farmers outside the group with a density of 0.005. The social networks that occur between these actors are intertwined due to the existence of kinship relationships, family or close friends who know each other among them. The relationship between family, family or close friends built with mutual trust make this network integrated.

scholarly journals Social Networks and Supply Chain Management in Fish Trade

SAGE Open ◽  
2020 ◽  
Vol 10 (2) ◽  
pp. 215824402093181
Author(s):  
Carmen Pedroza-Gutiérrez ◽  
Juan M. Hernández
Keyword(s):  
Supply Chain ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Real Life ◽  
Primary Data ◽  
Structured Interviews ◽  
Knowledge Based ◽  
The Relationship

This study aims to construct a theoretical framework to analyze the elements of the network structure and the relationship system within the seafood supply chain. The scope of the investigation is to evaluate how these elements influence the flow of products and the efficiency of the seafood supply chain and why these social interactions can create value and enhance competitive advantage. The model combines the resource- and knowledge-based view and the social network analysis applied to seafood supply chains. To demonstrate the application of the model, two theoretical examples and a real case study of the Mercado del Mar in Guadalajara, Mexico, are used. Primary data are obtained from semi-structured interviews, social network analysis metrics, and qualitative analysis. Findings are based on the analysis of theoretical examples and must be considered with caution. Nevertheless, the observations in the examples and case study provide new arguments to the relationship between the pattern of interrelationship and the efficiency of a supply chain. This study emphasizes the necessity of combining quantitative and qualitative analyses to understand and explain real-life supply networks.

Application of Computer System in the Study of Sociology

2014 ◽  
Vol 926-930 ◽  
pp. 1680-1683
Author(s):  
Ying Ming Xu ◽  
Shu Juan Jin
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Computer Algorithms ◽  
Useful Knowledge ◽  
Social Network Data ◽  
Analysis Task ◽  
Original Analysis ◽  
The Social ◽  
The Relationship

With the development of information technology, more and more data about social to be collected. If we can analyze them effectively, it will help people to understand sociological understanding, promoting the development of social science. But the increasing amount of data and analysis to put forward a huge challenge. Now the social networks have already surpassed the processing ability of the original analysis means, must use a more effective tool to complete the analysis task. The computer as a way of helping people from massive data to find the potential useful knowledge tools, play an important role in many fields. Social network analysis, also known as link mining, refers to the handling of the relationship between social network data in the computer method. In this paper, the methods of computer and the social network analysis was introduced in this paper and the computer algorithms are summarized in the application of social network analysis.

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