Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 378

The DOI matches its Crossref record.

Mapping the global Twitter heartbeat: The geography of Twitter

Open access
Leetaru, Kalev, Wang, Shaowen, Cao, Guofeng, Padmanabhan, Anand, Shook, Eric·2013·First Monday

Abstract

In just under seven years, Twitter has grown to count nearly 3% of the entire global population among its active users who have sent more than 170 billion 140-character messages. Today the service plays such a significant role in American culture that the Library of Congress has assembled a permanent archive of the site back to its first tweet, updated daily. With its open API, Twitter has become one of the most popular data sources for social research, yet the majority of the literature has focused on it as a text or network graph source, with only limited efforts to date focusing exclusively on the geography of Twitter, assessing the various sources of geographic information on the service and their accuracy. More than 3% of all tweets are found to have native location information available, while a naive geocoder based on a simple major cities gazetteer and relying on the user-provided Location and Profile fields is able to geolocate more than a third of all tweets with high accuracy when measured against the GPS-based baseline. Geographic proximity is found to play a minimal role both in who users communicate with and what they communicate about, providing evidence that social media is shifting the communicative landscape.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.5210/fm.v18i5.4366

Cites

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cited by

See all 378

Metadata

Authors
Leetaru, K., Wang, S., Cao, G., Padmanabhan, A., & Shook, E.
Venue
First Monday
Published
2013-04-22
ISSN
  • 1396-0458 (ISSN-L)
  • 1396-0466
OpenAlex
W2093588201
Cited by
378
References
0
FWCI
106.23
Type
journal article
Language
en
Open access
diamond

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Mapping the global Twitter heartbeat: The geography of Twitter. https://app.cochat.ai/papers/10.5210/fm.v18i5.4366
The paper
Leetaru, K., Wang, S., Cao, G., Padmanabhan, A., & Shook, E. (2013). Mapping the global Twitter heartbeat: The geography of Twitter. First Monday. https://doi.org/10.5210/fm.v18i5.4366

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.