Influenza Tweet Annotations

Copyright 2013 Alex Lamb, Michael Paul, Mark Dredze
Contact: Michael Paul <mpaul@cs.jhu.edu>

Please cite the following paper in any work that uses this material:

@InProceedings{lamb-paul-dredze-naacl-2013,
  author    = {Lamb, Alex and Paul, Michael J. and Dredze, Mark},
  title     = {Separating Fact from Fear: Tracking Flu Infections on Twitter},
  booktitle = {North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT 2013)},
  month     = {June},
  year      = {2013},
  url       = {http://www.aclweb.org/anthology/N/N13/N13-1097.pdf}
}

This data set contains the labels assigned to tweets, as described in
the paper above. These are tab-separated files, where the first column
is the tweet ID and the second column is a binary label. The labels are:

RelatedVsNotRelated:
 0: Not related to influenza
 1: Related to influenza

AwarenessVsInfection:
 0: Influenza infection
 1: Influenza awareness

SelfVsOthers:
 0: Others (the tweet describes someone else)
 1: Self (the tweet describes the author)

As per the Twitter guidelines, we are only releasing the IDs of the tweets
and not the content of the tweets. You can use these IDs to download the
corresponding tweets using the Twitter API. See:
https://dev.twitter.com/docs/api/1.1



