@inproceedings{59d24919a18b4f7fb9958521edbf5304,
title = "Evaluating the representativeness in the geographic distribution of twitter user population",
abstract = "Twitter data are becoming a Big Data stream and have drawn multidisciplinary interests to study population characteristics and social problems that cannot be measured well by traditional surveys. However, the use of Twitter data has been strongly resisted because of concerns about the representativeness of the population as we know little about the demographic characters of the users. It is critical to evaluate the extent to which Twitter users represent the population across different demographic groups. This study evaluates the representativeness and examines the geographic distributions of Twitter user population and its correspondence to the real population. By estimating Twitter user demographics for the contiguous U.S. in 2014, the preliminary results revealed both over- and under-representation of certain demographic groups against the real population at county-level. A representation index is used to assess the representativeness of Twitter samples geographically, which may help further studies to identify the determinants of biases.",
author = "Junjun Yin and Guangqing Chi and {Van Hook}, Jennifer",
note = "Publisher Copyright: {\textcopyright} 2018 Copyright is held by the owner/author(s).; 12th Workshop on Geographic Information Retrieval, GIR 2018 ; Conference date: 06-11-2018",
year = "2018",
month = nov,
day = "6",
doi = "10.1145/3281354.3281360",
language = "English (US)",
series = "Proceedings of the 12th Workshop on Geographic Information Retrieval, GIR 2018",
publisher = "Association for Computing Machinery, Inc",
editor = "Jones, {Christopher B.} and Purves, {Ross S.}",
booktitle = "Proceedings of the 12th Workshop on Geographic Information Retrieval, GIR 2018",
}