Evidence map›Paper›PMID 34458562›Full record

ArticleApplied network science2021

City consumption profile: a city perspective on the spending behavior of citizens.

Alessia Galdeman, Cheick T Ba, Matteo Zignani, Christian Quadri, Sabrina Gaito

Abstract read
In one paragraph

Article in Applied network science, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Alessia GaldemanDepartment of Computer Science, University of Milan, Milan, Italy.
Cheick T BaDepartment of Computer Science, University of Milan, Milan, Italy.
Matteo ZignaniDepartment of Computer Science, University of Milan, Milan, Italy.ORCID 0000-0002-4808-4106
Christian QuadriDepartment of Computer Science, University of Milan, Milan, Italy.
Sabrina GaitoDepartment of Computer Science, University of Milan, Milan, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In designing the city of the future, city managers and urban planners are driven by specific citizens' behaviors. In fact, economic and financial behaviors, and specifically, which goods and services citizens purchase and how they allocate their spending, are playing a central role in planning targeted services. In this context, cashless payments provide an invaluable data source to identify such spending behaviors. In this work, we propose a methodology to extract the consumption behaviors of a large sample of customers through credit card transaction data. The main outcome of the methodology is a concise representation of the economic behavior of people residing in a city, the so-called

Indexed as

Community detectionCustomer segmentationUrban computing

Identifiers

PMID34458562
PMCPMC8382214

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.