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37 Santa Clara High Tech. L. J. 119 (2021)
Copyrighting Copywrongs: An Empirical Analysis of Errors with Automated DMCA Takedown Notices

handle is hein.journals/sccj37 and id is 121 raw text is: COPYRIGHTING COPYWRONGS: AN EMPIRICAL
By Daniel Seng'
Under the Digital Millennium Copyright Act (DMCA),
reporters issuing takedown notices are required to identify the
infringed work and the infringing material and provide their contact
information (functional formalities), attest to the accuracy of such
information and their authority to act on behalf of the copyright owner,
and sign the notices (non-functional formalities). Online service
providers will evaluate such notices for compliance with these DMCA
formalities before acting on them. This paper seeks to answer questions
about the quality of takedown notices, especially those generated by
automated systems, which are increasingly being used by copyright
owners to detect instances of online infringement and issue takedown
notices on their behalf After parsing three million takedown notices
and more than eighty million takedown complaints served on Google
between 2011 and 2015, this paper analyzes each notice for errors.
This paper finds that almost all notices comply with the non-functional
formalities. However, at least 5.5% of all takedown notices between
1 Daniel Seng, Associate Professor, Faculty of Law, National University of
Singapore. I would like to thank Mark Lemley, Deborah Hensler, Phil Malone
and Maria Jose Cordero for their useful feedback and suggestions for an earlier
draft of this paper, which was entitled Trust But Verify. I would also like to
record my deepest thanks to Shaun Lim for his invaluable help in revising this
paper and updating the statistics with the porting of the Chilling Effects
database onto the Lumen platform. The original material for this paper based
on the Chilling Effects database was first presented at the 15th Year
Retrospective of the Digital Millennium Copyright Act, Santa Clara
University on March 15, 2013. It has since been updated with the dataset from
the Lumen database. I also wish to thank Adam Holland from the Berkman
Klein Centre for Internet & Society, Harvard University, for his kindness in
enabling me unprecedented access to the Lumen database for purposes of this
research. Funding support for the research that made this paper possible is
provided by the National University of Singapore through the Singapore
Ministry of Education Academic Research Fund Tier 1.


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