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Mapping Physician Twitter Networks: Describing How They Work as a First Step in Understanding Connectivity, Information Flow, and Message Diffusion
BACKGROUND: Twitter is becoming an important tool in medicine, but there is little information on Twitter metrics. In order to recommend best practices for information dissemination and diffusion, it is important to first study and analyze the networks. OBJECTIVE: This study describes the characteri...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
JMIR Publications Inc.
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4004136/ https://www.ncbi.nlm.nih.gov/pubmed/24733146 http://dx.doi.org/10.2196/jmir.3006 |
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author | Mishori, Ranit Singh, Lisa Oberoi Levy, Brendan Newport, Calvin |
author_facet | Mishori, Ranit Singh, Lisa Oberoi Levy, Brendan Newport, Calvin |
author_sort | Mishori, Ranit |
collection | PubMed |
description | BACKGROUND: Twitter is becoming an important tool in medicine, but there is little information on Twitter metrics. In order to recommend best practices for information dissemination and diffusion, it is important to first study and analyze the networks. OBJECTIVE: This study describes the characteristics of four medical networks, analyzes their theoretical dissemination potential, their actual dissemination, and the propagation and distribution of tweets. METHODS: Open Twitter data was used to characterize four networks: the American Medical Association (AMA), the American Academy of Family Physicians (AAFP), the American Academy of Pediatrics (AAP), and the American College of Physicians (ACP). Data were collected between July 2012 and September 2012. Visualization was used to understand the follower overlap between the groups. Actual flow of the tweets for each group was assessed. Tweets were examined using Topsy, a Twitter data aggregator. RESULTS: The theoretical information dissemination potential for the groups is large. A collective community is emerging, where large percentages of individuals are following more than one of the groups. The overlap across groups is small, indicating a limited amount of community cohesion and cross-fertilization. The AMA followers’ network is not as active as the other networks. The AMA posted the largest number of tweets while the AAP posted the fewest. The number of retweets for each organization was low indicating dissemination that is far below its potential. CONCLUSIONS: To increase the dissemination potential, medical groups should develop a more cohesive community of shared followers. Tweet content must be engaging to provide a hook for retweeting and reaching potential audience. Next steps call for content analysis, assessment of the behavior and actions of the messengers and the recipients, and a larger-scale study that considers other medical groups using Twitter. |
format | Online Article Text |
id | pubmed-4004136 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | JMIR Publications Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-40041362014-04-30 Mapping Physician Twitter Networks: Describing How They Work as a First Step in Understanding Connectivity, Information Flow, and Message Diffusion Mishori, Ranit Singh, Lisa Oberoi Levy, Brendan Newport, Calvin J Med Internet Res Original Paper BACKGROUND: Twitter is becoming an important tool in medicine, but there is little information on Twitter metrics. In order to recommend best practices for information dissemination and diffusion, it is important to first study and analyze the networks. OBJECTIVE: This study describes the characteristics of four medical networks, analyzes their theoretical dissemination potential, their actual dissemination, and the propagation and distribution of tweets. METHODS: Open Twitter data was used to characterize four networks: the American Medical Association (AMA), the American Academy of Family Physicians (AAFP), the American Academy of Pediatrics (AAP), and the American College of Physicians (ACP). Data were collected between July 2012 and September 2012. Visualization was used to understand the follower overlap between the groups. Actual flow of the tweets for each group was assessed. Tweets were examined using Topsy, a Twitter data aggregator. RESULTS: The theoretical information dissemination potential for the groups is large. A collective community is emerging, where large percentages of individuals are following more than one of the groups. The overlap across groups is small, indicating a limited amount of community cohesion and cross-fertilization. The AMA followers’ network is not as active as the other networks. The AMA posted the largest number of tweets while the AAP posted the fewest. The number of retweets for each organization was low indicating dissemination that is far below its potential. CONCLUSIONS: To increase the dissemination potential, medical groups should develop a more cohesive community of shared followers. Tweet content must be engaging to provide a hook for retweeting and reaching potential audience. Next steps call for content analysis, assessment of the behavior and actions of the messengers and the recipients, and a larger-scale study that considers other medical groups using Twitter. JMIR Publications Inc. 2014-04-14 /pmc/articles/PMC4004136/ /pubmed/24733146 http://dx.doi.org/10.2196/jmir.3006 Text en ©Ranit Mishori, Lisa Oberoi Singh, Brendan Levy, Calvin Newport. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 14.04.2014. http://creativecommons.org/licenses/by/2.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on http://www.jmir.org/, as well as this copyright and license information must be included. |
spellingShingle | Original Paper Mishori, Ranit Singh, Lisa Oberoi Levy, Brendan Newport, Calvin Mapping Physician Twitter Networks: Describing How They Work as a First Step in Understanding Connectivity, Information Flow, and Message Diffusion |
title | Mapping Physician Twitter Networks: Describing How They Work as a First Step in Understanding Connectivity, Information Flow, and Message Diffusion |
title_full | Mapping Physician Twitter Networks: Describing How They Work as a First Step in Understanding Connectivity, Information Flow, and Message Diffusion |
title_fullStr | Mapping Physician Twitter Networks: Describing How They Work as a First Step in Understanding Connectivity, Information Flow, and Message Diffusion |
title_full_unstemmed | Mapping Physician Twitter Networks: Describing How They Work as a First Step in Understanding Connectivity, Information Flow, and Message Diffusion |
title_short | Mapping Physician Twitter Networks: Describing How They Work as a First Step in Understanding Connectivity, Information Flow, and Message Diffusion |
title_sort | mapping physician twitter networks: describing how they work as a first step in understanding connectivity, information flow, and message diffusion |
topic | Original Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4004136/ https://www.ncbi.nlm.nih.gov/pubmed/24733146 http://dx.doi.org/10.2196/jmir.3006 |
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