The purpose of this study is to detect project teams in a group. A key point in considering group's relationships is the reciprocal influence, whereby group's members influence each other. There was conducted a survey based on reciprocal nomination method, and then a social network was constructed. Participants were first-year bachelor students of Tomsk Polytechnic University. Various social network analysis algorithms were used to cluster network in communities. The results of analysis were discussed with the teachers and students, and then detected community teams were adjusted within the key actors of group. The results of the study may be used to create project teams, which can make successful collective actions in educational projects.
|Журнал||CEUR Workshop Proceedings|
|Состояние||Опубликовано - 2016|
|Событие||5th International Conference on Analysis of Images, Social Networks and Texts, AIST 2016 - Yekaterinburg, Российская Федерация|
Продолжительность: 6 апр 2016 → 8 апр 2016
ASJC Scopus subject areas
- Computer Science(all)