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Title: Twitter Geolocation: A Hybrid Approach

Authors:
 [1];  [1];  [1];  [2];  [2]
  1. North Carolina State University, Raleigh, NC
  2. Los Alamos National Laboratory, Los Alamos, NM
Publication Date:
Research Org.:
North Carolina State Univ., Raleigh, NC (United States); Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
Sponsoring Org.:
USDOE National Nuclear Security Administration (NNSA), Office of Nonproliferation and Verification Research and Development (NA-22); National Science Foundation (NSF)
OSTI Identifier:
1467267
Report Number(s):
LA-UR-24700
Journal ID: ISSN 1556-4681
Grant/Contract Number:  
NA0002576; DGE-1633587; AC52-06NA25396
Resource Type:
Accepted Manuscript
Journal Name:
ACM Transactions on Knowledge Discovery from Data
Additional Journal Information:
Journal Volume: 12; Journal Issue: 3; Journal ID: ISSN 1556-4681
Publisher:
Association for Computing Machinery
Country of Publication:
United States
Language:
English

Citation Formats

Bakerman, Jordan, Pazdernik, Karl, Wilson, Alyson, Fairchild, Geoffrey, and Bahran, Rian. Twitter Geolocation: A Hybrid Approach. United States: N. p., 2018. Web. doi:10.1145/3178112.
Bakerman, Jordan, Pazdernik, Karl, Wilson, Alyson, Fairchild, Geoffrey, & Bahran, Rian. Twitter Geolocation: A Hybrid Approach. United States. doi:10.1145/3178112.
Bakerman, Jordan, Pazdernik, Karl, Wilson, Alyson, Fairchild, Geoffrey, and Bahran, Rian. Fri . "Twitter Geolocation: A Hybrid Approach". United States. doi:10.1145/3178112. https://www.osti.gov/servlets/purl/1467267.
@article{osti_1467267,
title = {Twitter Geolocation: A Hybrid Approach},
author = {Bakerman, Jordan and Pazdernik, Karl and Wilson, Alyson and Fairchild, Geoffrey and Bahran, Rian},
abstractNote = {},
doi = {10.1145/3178112},
journal = {ACM Transactions on Knowledge Discovery from Data},
number = 3,
volume = 12,
place = {United States},
year = {2018},
month = {3}
}

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