Learning in social networks: analyzing the Twitter data

• Grant number: 11/10297-5
• Support Opportunities: Scholarships in Brazil - Scientific Initiation
• Start date: September 01, 2011
• End date: November 30, 2012
• Field of knowledge: Physical Sciences and Mathematics - Computer Science - Computing Methodologies and Techniques
• Principal Investigator: Luciana Aparecida Martinez Zaina
• Grantee: Guilherme Martins Torres
• Host Institution: Centro de Ciências e Tecnologias para a Sustentabilidade (CCTS). Universidade Federal de São Carlos (UFSCAR). Sorocaba , SP, Brazil

Abstract

The development of online social network applications have increased in the past few years through the emerging Web 2.0, improving the socialization through communication and collaboration tools. In this context, the e-learning area has shown the interest in adopting social softwares as wikis, blogs and social networks to support the building of knowledge. Among the social online environments, the Twitter has been highlighted as a communication, collaboration and sharing ware of ideas. The analysis of messages posted in Twitter (called tweets) allows the extraction of information about the number of posted messages linked to a subject, the messages resent and replied and so one. Messages' analysis can usually be supported by text mining techniques in terms of observing text written patterns as for instance the occurrences of keywords. The goal of this work is to collect and to analyze Twitter messages used in educational purpose, checking the cluster of students and teacher by common interests. It may verified by a set of relevant keywords in a context that are studied in the subjects. The tweet relevance and the interest of a group will be noticed through the application of mining text techniques in the tweets posted by the teacher, checking retweets and new tweets send by a student from the teacher posts. (AU)