JOURNAL ARTICLE

Twitter content classification

Stephen Dann

Year: 2010 Journal:   First Monday   Publisher: University of Illinois at Chicago

Abstract

This paper delivers a new Twitter content classification framework based sixteen existing Twitter studies and a grounded theory analysis of a personal Twitter history. It expands the existing understanding of Twitter as a multifunction tool for personal, profession, commercial and phatic communications with a split level classification scheme that offers broad categorization and specific sub categories for deeper insight into the real world application of the service.

Keywords:
Categorization Computer science World Wide Web Social media Classification scheme Service (business) Grounded theory Data science Scheme (mathematics) Content (measure theory) Information retrieval Sociology Artificial intelligence Business Qualitative research Mathematics Marketing Social science

Metrics

123
Cited By
8.66
FWCI (Field Weighted Citation Impact)
0
Refs
0.98
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Digital Communication and Language
Physical Sciences →  Computer Science →  Human-Computer Interaction
© 2026 ScienceGate Book Chapters — All rights reserved.