Paper: Authorship Attribution of Micro-Messages

ACL ID D13-1193
Title Authorship Attribution of Micro-Messages
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2013
Authors

Work on authorship attribution has tradition- ally focused on long texts. In this work, we tackle the question of whether the author of a very short text can be successfully iden- tified. We use Twitter as an experimental testbed. We introduce the concept of an au- thor?s unique ?signature?, and show that such signatures are typical of many authors when writing very short texts. We also present a new authorship attribution feature (?flexible pat- terns?) and demonstrate a significant improve- ment over our baselines. Our results show that the author of a single tweet can be identified with good accuracy in an array of flavors of the authorship attribution task.