Predicting demographics of high-resolution geographies with geotagged tweets

Omar Montasser, Daniel Kifer

Research output: Contribution to conferencePaper

3 Citations (Scopus)

Abstract

In this paper, we consider the problem of predicting demographics of geographic units given geotagged Tweets that are composed within these units. Traditional survey methods that offer demographics estimates are usually limited in terms of geographic resolution, geographic boundaries, and time intervals. Thus, it would be highly useful to develop computational methods that can complement traditional survey methods by offering demographics estimates at finer geographic resolutions, with flexible geographic boundaries (i.e. not confined to administrative boundaries), and at different time intervals. While prior work has focused on predicting demographics and health statistics at relatively coarse geographic resolutions such as the county-level or state-level, we introduce an approach to predict demographics at finer geographic resolutions such as the blockgroup-level. For the task of predicting gender and race/ethnicity counts at the blockgrouplevel, an approach adapted from prior work to our problem achieves an average correlation of 0.389 (gender) and 0.569 (race) on a held-out test dataset. Our approach outperforms this prior approach with an average correlation of 0.671 (gender) and 0.692 (race).

Original languageEnglish (US)
Pages1460-1466
Number of pages7
StatePublished - Jan 1 2017
Event31st AAAI Conference on Artificial Intelligence, AAAI 2017 - San Francisco, United States
Duration: Feb 4 2017Feb 10 2017

Other

Other31st AAAI Conference on Artificial Intelligence, AAAI 2017
CountryUnited States
CitySan Francisco
Period2/4/172/10/17

Fingerprint

Computational methods
Health
Statistics

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence

Cite this

Montasser, O., & Kifer, D. (2017). Predicting demographics of high-resolution geographies with geotagged tweets. 1460-1466. Paper presented at 31st AAAI Conference on Artificial Intelligence, AAAI 2017, San Francisco, United States.
Montasser, Omar ; Kifer, Daniel. / Predicting demographics of high-resolution geographies with geotagged tweets. Paper presented at 31st AAAI Conference on Artificial Intelligence, AAAI 2017, San Francisco, United States.7 p.
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Montasser, O & Kifer, D 2017, 'Predicting demographics of high-resolution geographies with geotagged tweets' Paper presented at 31st AAAI Conference on Artificial Intelligence, AAAI 2017, San Francisco, United States, 2/4/17 - 2/10/17, pp. 1460-1466.

Predicting demographics of high-resolution geographies with geotagged tweets. / Montasser, Omar; Kifer, Daniel.

2017. 1460-1466 Paper presented at 31st AAAI Conference on Artificial Intelligence, AAAI 2017, San Francisco, United States.

Research output: Contribution to conferencePaper

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Montasser O, Kifer D. Predicting demographics of high-resolution geographies with geotagged tweets. 2017. Paper presented at 31st AAAI Conference on Artificial Intelligence, AAAI 2017, San Francisco, United States.