Abstract
Work on authorship attribution has traditionally focused on long texts. In this work, we tackle the question of whether the author of a very short text can be successfully identified. We use Twitter as an experimental testbed. We introduce the concept of an author'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 patterns") and demonstrate a significant improvement 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.
| Original language | English |
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| Title of host publication | EMNLP 2013 - 2013 Conference on Empirical Methods in Natural Language Processing, Proceedings of the Conference |
| Publisher | Association for Computational Linguistics (ACL) |
| Pages | 1880-1891 |
| Number of pages | 12 |
| ISBN (Electronic) | 9781937284978 |
| State | Published - 2013 |
| Event | 2013 Conference on Empirical Methods in Natural Language Processing, EMNLP 2013 - Seattle, United States Duration: 18 Oct 2013 → 21 Oct 2013 |
Publication series
| Name | EMNLP 2013 - 2013 Conference on Empirical Methods in Natural Language Processing, Proceedings of the Conference |
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Conference
| Conference | 2013 Conference on Empirical Methods in Natural Language Processing, EMNLP 2013 |
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| Country/Territory | United States |
| City | Seattle |
| Period | 18/10/13 → 21/10/13 |
Bibliographical note
Publisher Copyright:© 2013 Association for Computational Linguistics.
Funding
The authors wish to acknowledge the work done by Mariam Amer and Arij Nabil, Graduate Research Assistants at the American University in Cairo in the development work of this paper.
| Funders | Funder number |
|---|---|
| American University in Cairo |