Summary of the paper
| Title | A New Twitter Verb Lexicon for Natural Language Processing |
|---|---|
| Authors | Jennifer Williams and Graham Katz |
| Abstract | We describe in-progress work on the creation of a new lexical resource that contains a list of 486 verbs annotated with quantified temporal durations for the events that they describe. This resource is being compiled from more than 14 million tweets from the Twitter microblogging site. We are creating this lexicon of verbs and typical durations to address a gap in the available information that is represented in existing research. The data that is contained in this lexical resource is unlike any existing resources, which have been traditionally comprised from literature excerpts, news stories, and full-length weblogs. The kind of knowledge about how long an event lasts is crucial for natural language processing and is especially useful when the temporal duration of an event is implied. We are using data from Twitter because Twitter is a rich resource since people are publicly posting about real events and real durations of those events throughout the day. |
| Topics | Lexicon, lexical database, Information Extraction, Information Retrieval, Corpus (creation, annotation, etc.) |
Full paper  |
A New Twitter Verb Lexicon for Natural Language Processing |
| Bibtex | @InProceedings{WILLIAMS12.1076, author = {Jennifer Williams and Graham Katz}, title = {A New Twitter Verb Lexicon for Natural Language Processing}, booktitle = {Proceedings of the Eight International Conference on Language Resources and Evaluation (LREC'12)}, year = {2012}, month = {may}, date = {23-25}, address = {Istanbul, Turkey}, editor = {Nicoletta Calzolari (Conference Chair) and Khalid Choukri and Thierry Declerck and Mehmet Uğur Doğan and Bente Maegaard and Joseph Mariani and Asuncion Moreno and Jan Odijk and Stelios Piperidis}, publisher = {European Language Resources Association (ELRA)}, isbn = {978-2-9517408-7-7}, language = {english} } |