Twitter User Classification using Ambient Metadata

TL;DR

This paper explores the use of ambient metadata, especially profile descriptions, to classify Twitter users effectively, demonstrating the potential of metadata features for user categorization.

Contribution

It introduces a method leveraging profile description metadata for user classification on Twitter, highlighting its effectiveness compared to other features.

Findings

Profile description metadata is effective for user classification.

Ambient metadata can significantly improve classification accuracy.

Metadata features outperform some traditional user features.

Abstract

Microblogging websites, especially Twitter have become an important means of communication, in today's time. Often these services have been found to be faster than conventional news services. With millions of users, a need was felt to classify users based on ambient metadata associated with their user accounts. We particularly look at the effectiveness of the profile description field in order to carry out the task of user classification. Our results show that such metadata can be an effective feature for any classification task.