Classification and Analysis of Personal and Commercial CBD Tweets

Jason S. Turner; Mehmed M. Kantardzic; Rachel Vickers-Smith

doi:10.1007/978-3-030-72805-2_10

Classification and Analysis of Personal and Commercial CBD Tweets

Jason S. Turner
, Mehmed M. Kantardzic
, Rachel Vickers-Smith

Producción científica: Conference contribution › revisión exhaustiva

Resumen

This study analyzes the differences in terms regarding cannabidiol (CBD) expressed by commercial sellers and personal users on Twitter. It demonstrates that data from social networks can be used by public health and medical researchers to compare the medical conditions targeted by those selling loosely-regulated substances such as CBD against the medical conditions that patients themselves are commonly treating with CBD. We collected 567,850 tweets by searching Twitter with the Tweepy Python package using the terms CBD and cannabidiol, and annotated a sample of 5,496 tweets to distinguish between personal use CBD tweets and commercial/sales-related CBD tweets. We used this sample to train two binary text classifiers to create two corpora of 169,876 personal use and 148,866 commercial/sales. Using medical, standard, and slang dictionaries, we then identified and compared the most frequently occurring medical conditions, symptoms, side effects, body parts, and other substances referenced in both corpora.

Idioma original	English
Título de la publicación alojada	Mediterranean Forum – Data Science Conference - First International Conference, MeFDATA 2020, Revised Selected Papers
Editores	Jasminka Hasic Telalovic, Mehmed Kantardzic
Páginas	139-150
Número de páginas	12
DOI	https://doi.org/10.1007/978-3-030-72805-2_10
Estado	Published - 2021
Evento	1st Mediterranean Forum - Data Science Conference, MeFDATA 2020 - Virtual, Online Duración: oct 24 2020 → oct 24 2020

Serie de la publicación

Nombre	Communications in Computer and Information Science
Volumen	1343 CCIS
ISSN (versión impresa)	1865-0929
ISSN (versión digital)	1865-0937

Conference

Conference	1st Mediterranean Forum - Data Science Conference, MeFDATA 2020
Ciudad	Virtual, Online
Período	10/24/20 → 10/24/20

Nota bibliográfica

Publisher Copyright:
© 2021, Springer Nature Switzerland AG.

ODS de las Naciones Unidas

Este resultado contribuye a los siguientes Objetivos de Desarrollo Sostenible

Good health and well being

ASJC Scopus subject areas

General Computer Science
General Mathematics

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10.1007/978-3-030-72805-2_10

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Turner, J. S., Kantardzic, M. M., & Vickers-Smith, R. (2021). Classification and Analysis of Personal and Commercial CBD Tweets. En J. Hasic Telalovic, & M. Kantardzic (Eds.), Mediterranean Forum – Data Science Conference - First International Conference, MeFDATA 2020, Revised Selected Papers (pp. 139-150). (Communications in Computer and Information Science; Vol. 1343 CCIS). https://doi.org/10.1007/978-3-030-72805-2_10

Turner, Jason S. ; Kantardzic, Mehmed M. ; Vickers-Smith, Rachel. / Classification and Analysis of Personal and Commercial CBD Tweets. Mediterranean Forum – Data Science Conference - First International Conference, MeFDATA 2020, Revised Selected Papers. editor / Jasminka Hasic Telalovic ; Mehmed Kantardzic. 2021. pp. 139-150 (Communications in Computer and Information Science).

@inproceedings{a53459d7e88745f4ab7ebef522e31fc6,

title = "Classification and Analysis of Personal and Commercial CBD Tweets",

abstract = "This study analyzes the differences in terms regarding cannabidiol (CBD) expressed by commercial sellers and personal users on Twitter. It demonstrates that data from social networks can be used by public health and medical researchers to compare the medical conditions targeted by those selling loosely-regulated substances such as CBD against the medical conditions that patients themselves are commonly treating with CBD. We collected 567,850 tweets by searching Twitter with the Tweepy Python package using the terms CBD and cannabidiol, and annotated a sample of 5,496 tweets to distinguish between personal use CBD tweets and commercial/sales-related CBD tweets. We used this sample to train two binary text classifiers to create two corpora of 169,876 personal use and 148,866 commercial/sales. Using medical, standard, and slang dictionaries, we then identified and compared the most frequently occurring medical conditions, symptoms, side effects, body parts, and other substances referenced in both corpora.",

keywords = "Cannabis, Text classification, Text mining",

author = "Turner, \{Jason S.\} and Kantardzic, \{Mehmed M.\} and Rachel Vickers-Smith",

note = "Publisher Copyright: {\textcopyright} 2021, Springer Nature Switzerland AG.; 1st Mediterranean Forum - Data Science Conference, MeFDATA 2020 ; Conference date: 24-10-2020 Through 24-10-2020",

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doi = "10.1007/978-3-030-72805-2\_10",

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Turner, JS, Kantardzic, MM & Vickers-Smith, R 2021, Classification and Analysis of Personal and Commercial CBD Tweets. En J Hasic Telalovic & M Kantardzic (eds.), Mediterranean Forum – Data Science Conference - First International Conference, MeFDATA 2020, Revised Selected Papers. Communications in Computer and Information Science, vol. 1343 CCIS, pp. 139-150, 1st Mediterranean Forum - Data Science Conference, MeFDATA 2020, Virtual, Online, 10/24/20. https://doi.org/10.1007/978-3-030-72805-2_10

Classification and Analysis of Personal and Commercial CBD Tweets. / Turner, Jason S.; Kantardzic, Mehmed M.; Vickers-Smith, Rachel.
Mediterranean Forum – Data Science Conference - First International Conference, MeFDATA 2020, Revised Selected Papers. ed. / Jasminka Hasic Telalovic; Mehmed Kantardzic. 2021. p. 139-150 (Communications in Computer and Information Science; Vol. 1343 CCIS).

Producción científica: Conference contribution › revisión exhaustiva

TY - GEN

T1 - Classification and Analysis of Personal and Commercial CBD Tweets

AU - Turner, Jason S.

AU - Kantardzic, Mehmed M.

AU - Vickers-Smith, Rachel

PY - 2021

Y1 - 2021

N2 - This study analyzes the differences in terms regarding cannabidiol (CBD) expressed by commercial sellers and personal users on Twitter. It demonstrates that data from social networks can be used by public health and medical researchers to compare the medical conditions targeted by those selling loosely-regulated substances such as CBD against the medical conditions that patients themselves are commonly treating with CBD. We collected 567,850 tweets by searching Twitter with the Tweepy Python package using the terms CBD and cannabidiol, and annotated a sample of 5,496 tweets to distinguish between personal use CBD tweets and commercial/sales-related CBD tweets. We used this sample to train two binary text classifiers to create two corpora of 169,876 personal use and 148,866 commercial/sales. Using medical, standard, and slang dictionaries, we then identified and compared the most frequently occurring medical conditions, symptoms, side effects, body parts, and other substances referenced in both corpora.

AB - This study analyzes the differences in terms regarding cannabidiol (CBD) expressed by commercial sellers and personal users on Twitter. It demonstrates that data from social networks can be used by public health and medical researchers to compare the medical conditions targeted by those selling loosely-regulated substances such as CBD against the medical conditions that patients themselves are commonly treating with CBD. We collected 567,850 tweets by searching Twitter with the Tweepy Python package using the terms CBD and cannabidiol, and annotated a sample of 5,496 tweets to distinguish between personal use CBD tweets and commercial/sales-related CBD tweets. We used this sample to train two binary text classifiers to create two corpora of 169,876 personal use and 148,866 commercial/sales. Using medical, standard, and slang dictionaries, we then identified and compared the most frequently occurring medical conditions, symptoms, side effects, body parts, and other substances referenced in both corpora.

KW - Cannabis

KW - Text classification

KW - Text mining

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UR - https://www.scopus.com/pages/publications/85107424581#tab=citedBy

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DO - 10.1007/978-3-030-72805-2_10

M3 - Conference contribution

AN - SCOPUS:85107424581

SN - 9783030728045

T3 - Communications in Computer and Information Science

SP - 139

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BT - Mediterranean Forum – Data Science Conference - First International Conference, MeFDATA 2020, Revised Selected Papers

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A2 - Kantardzic, Mehmed

T2 - 1st Mediterranean Forum - Data Science Conference, MeFDATA 2020

Y2 - 24 October 2020 through 24 October 2020

ER -

Turner JS, Kantardzic MM, Vickers-Smith R. Classification and Analysis of Personal and Commercial CBD Tweets. En Hasic Telalovic J, Kantardzic M, editores, Mediterranean Forum – Data Science Conference - First International Conference, MeFDATA 2020, Revised Selected Papers. 2021. p. 139-150. (Communications in Computer and Information Science). doi: 10.1007/978-3-030-72805-2_10

Classification and Analysis of Personal and Commercial CBD Tweets

Resumen

Serie de la publicación

Conference

Nota bibliográfica

ODS de las Naciones Unidas

ASJC Scopus subject areas

Acceder al documento

Otros archivos y enlaces

Huella

Citar esto