iParasitology: Mining the Internet to Test Parasitological Hypotheses

Robert Poulin; Jerusha Bennett; Antoine Filion; Upendra Raj Bhattarai; Xuhong Chai; Daniela de Angeli Dutra; Erica Donlon; Jean-François Doherty; Fátima Jorge; Marin Milotic; Eunji Park; Amandine Sabadel; Leighton J Thomas

doi:10.1016/j.pt.2021.01.003

iParasitology: Mining the Internet to Test Parasitological Hypotheses

Robert Poulin, Jerusha Bennett, Antoine Filion, Upendra Raj Bhattarai, Xuhong Chai, Daniela de Angeli Dutra, Erica Donlon, Jean-François Doherty, Fátima Jorge, Marin Milotic, Eunji Park, Amandine Sabadel, Leighton J Thomas

University of Otago

Research output: Contribution to journal › Article › peer-review

Abstract

Digital data (internet queries, page views, social media posts, images) are accumulating online at increasing rates. Tools for compiling these data and extracting their metadata are now readily available. We highlight the possibilities and limitations of internet data to reveal patterns in host-parasite interactions and encourage parasitologists to embrace iParasitology.

Original language	English
Pages (from-to)	267-272
Number of pages	6
Journal	Trends in Parasitology
Volume	37
Issue number	4
Early online date	10 Mar 2021
DOIs	https://doi.org/10.1016/j.pt.2021.01.003
Publication status	Published - 1 Apr 2021
Externally published	Yes

Keywords

Data Mining/trends
Host-Parasite Interactions
Internet
Parasitology/methods

Access to Document

10.1016/j.pt.2021.01.003

Cite this

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title = "iParasitology: Mining the Internet to Test Parasitological Hypotheses",

abstract = "Digital data (internet queries, page views, social media posts, images) are accumulating online at increasing rates. Tools for compiling these data and extracting their metadata are now readily available. We highlight the possibilities and limitations of internet data to reveal patterns in host-parasite interactions and encourage parasitologists to embrace iParasitology.",

keywords = "Data Mining/trends, Host-Parasite Interactions, Internet, Parasitology/methods",

author = "Robert Poulin and Jerusha Bennett and Antoine Filion and Bhattarai, \{Upendra Raj\} and Xuhong Chai and \{de Angeli Dutra\}, Daniela and Erica Donlon and Jean-Fran{\c c}ois Doherty and F{\'a}tima Jorge and Marin Milotic and Eunji Park and Amandine Sabadel and Thomas, \{Leighton J\}",

year = "2021",

month = apr,

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doi = "10.1016/j.pt.2021.01.003",

language = "English",

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TY - JOUR

T1 - iParasitology

T2 - Mining the Internet to Test Parasitological Hypotheses

AU - Poulin, Robert

AU - Bennett, Jerusha

AU - Filion, Antoine

AU - Bhattarai, Upendra Raj

AU - Chai, Xuhong

AU - de Angeli Dutra, Daniela

AU - Donlon, Erica

AU - Doherty, Jean-François

AU - Jorge, Fátima

AU - Milotic, Marin

AU - Park, Eunji

AU - Sabadel, Amandine

AU - Thomas, Leighton J

PY - 2021/4/1

Y1 - 2021/4/1

N2 - Digital data (internet queries, page views, social media posts, images) are accumulating online at increasing rates. Tools for compiling these data and extracting their metadata are now readily available. We highlight the possibilities and limitations of internet data to reveal patterns in host-parasite interactions and encourage parasitologists to embrace iParasitology.

AB - Digital data (internet queries, page views, social media posts, images) are accumulating online at increasing rates. Tools for compiling these data and extracting their metadata are now readily available. We highlight the possibilities and limitations of internet data to reveal patterns in host-parasite interactions and encourage parasitologists to embrace iParasitology.

KW - Data Mining/trends

KW - Host-Parasite Interactions

KW - Internet

KW - Parasitology/methods

U2 - 10.1016/j.pt.2021.01.003

DO - 10.1016/j.pt.2021.01.003

M3 - Article

C2 - 33547010

SN - 1471-4922

VL - 37

SP - 267

EP - 272

JO - Trends in Parasitology

JF - Trends in Parasitology

IS - 4

ER -

iParasitology: Mining the Internet to Test Parasitological Hypotheses

Abstract

Keywords

Access to Document

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Cite this