Disaster response aided by tweet classification with a domain adaptation approach-Reference-Cited by-同舟云学术

Disaster response aided by tweet classification with a domain adaptation approach

Published:2017-09-04 Issue:1 Volume:26 Page:16-27
ISSN:0966-0879
Container-title:Journal of Contingencies and Crisis Management
language:en
Short-container-title:J Contingencies and Crisis Management

Author:

Li Hongmin¹,Caragea Doina¹,Caragea Cornelia²,Herndon Nic³

Affiliation:

1. Department of Computer Science Kansas State University Manhattan KS USA

2. Department of Computer Science and Engineering University of North Texas Denton TX USA

3. Department of Ecology and Evolutionary Biology University of Connecticut Storrs CT USA

Funder

National Science Foundation

Publisher

Wiley

Subject

Management, Monitoring, Policy and Law,Management Information Systems

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1111/1468-5973.12194

Reference58 articles.

1. Ashktorab Z. Brown C. Nandi M. &Culotta A.(2014). Tweedr: Mining Twitter to inform disaster response. InProceedings of 11th International Conference on Information Systems for Crisis Response and Management (ISCRAM 2014)(pp.354–358) University Park PA USA.

2. BBC Trending(2015).BBC News. Retrieved fromhttp://www.bbc.com/news/blogs-trending-34836214

3. An Overview of Sentiment Analysis in Social Media and Its Applications in Disaster Relief

4. Combining labeled and unlabeled data with co-training

5. Caragea C. Silvescu A. &Tapia A. H.(2016). Identifying informative messages in disaster events using convolutional neural networks. InProceedings of 13th International Conference on Information Systems for Crisis Response and Management (ISCRAM 2016). Rio de Janeiro Brazil May 2016.

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