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JMIR Nursing logoLink to JMIR Nursing
. 2021 Apr 20;4(2):e25114. doi: 10.2196/25114

Comparison of Intercom and Megaphone Hashtags Using Four Years of Tweets From the Top 44 Schools of Nursing: Thematic Analysis

Kimberly Acquaviva 1,
Editor: Gunther Eysenbach
Reviewed by: Richard Booth, Ari-Matti Auvinen, Ivanna Shubina
PMCID: PMC8279434  PMID: 34345795

Abstract

Background

When this study began in 2018, I sought to determine the extent to which the top 50 schools of nursing were using hashtags that could attract attention from journalists on Twitter. In December 2020, the timeframe was expanded to encompass 2 more years of data, and an analysis was conducted of the types of hashtags used.

Objective

The study attempted to answer the following question: to what extent are top-ranked schools of nursing using hashtags that could attract attention from journalists, policy makers, and the public on Twitter?

Methods

In February 2018, 47 of the top 50 schools of nursing had public Twitter accounts. The most recent 3200 tweets were extracted from each account and analyzed. There were 31,762 tweets in the time period covered (September 29, 2016, through February 22, 2018). After 13,429 retweets were excluded, 18,333 tweets remained. In December 2020, 44 of the original 47 schools of nursing still had public Twitter accounts under the same name used in the first phase of the study. Three accounts that were no longer active were removed from the 2016-2018 data set, resulting in 16,939 tweets from 44 schools of nursing. The Twitter data for the 44 schools of nursing were obtained for the time period covered in the second phase of the study (February 23, 2018, through December 13, 2020), and the most recent 3200 tweets were extracted from each of the accounts. On excluding retweets, there were 40,368 tweets in the 2018-2020 data set. The 2016-2018 data set containing 16,939 tweets was merged with the 2018-2020 data set containing 40,368 tweets, resulting in 57,307 tweets in the 2016-2020 data set.

Results

Each hashtag used 100 times or more in the 2016-2020 data set was categorized as one of the following seven types: nursing, school, conference or tweet chat, health, illness/disease/condition, population, and something else. These types were then broken down into the following two categories: intercom hashtags and megaphone hashtags. Approximately 83% of the time, schools of nursing used intercom hashtags (inward-facing hashtags focused on in-group discussion within and about the profession). Schools of nursing rarely used outward-facing megaphone hashtags. There was no discernible shift in the way that schools of nursing used hashtags after the publication of The Woodhull Study Revisited.

Conclusions

Top schools of nursing use hashtags more like intercoms to communicate with other nurses rather than megaphones to invite attention from journalists, policy makers, and the public. If schools of nursing want the media to showcase their faculty members as experts, they need to increase their use of megaphone hashtags to connect the work of their faculty with topics of interest to the public.

Keywords: Twitter, hashtag, nurses, media, intercom hashtag, megaphone hashtag

Introduction

Twitter is a microblogging website where users can post “tweets” (brief messages, images, and videos) to share with “followers” (people who have chosen to follow their Twitter account). Hashtags are words or phrases (without spaces) that are preceded by a pound sign (#) [1]. Hashtags first came into use on Twitter in 2007 when a user named Chris Messina put forward a proposal for “…improving contextualization, content filtering, and exploratory serendipity within Twitter” [2]. In his proposal, Messina wrote that his primary interest was “simply having a better eavesdropping experience on Twitter” [2]. In 2018, hashtags were widely used on Twitter to make tweets easy to find for other Twitter users interested in a given topic.

When the landmark Woodhull Study on Nursing and the Media was published in 1998, the voices and faces of nurses were found to be largely absent from news stories [3]. Mary Chaffee wrote that “[t]his lack of visibility limits nursing’s ability to communicate important health information, impedes nursing’s ability to define its role and contributions in the health care delivery system, and restricts nursing’s ability to advocate for health policy” [4]. Because Twitter was not launched until 8 years after the Woodhull Study was conducted, the researchers obviously could not look at Twitter data in their analysis. Shattell and Darmoc argue that nurses should consider using Twitter to make their “practical, real-life knowledge or…research findings or insights on current issues… available for the public” and to “harness attention from some more traditional media sources” [5]. While there is an abundance of research regarding the use of hashtags by health care professionals on Twitter [6-10], little is known about the ways in which schools of nursing used Twitter to invite attention from and engagement with journalists, policy makers, and the general public in the 2 years before The Woodhull Study Revisited was published in September 2018 and the 2 years after its publication. This study seeks to fill this gap.

When this study began in 2018 as a last-minute addition to The Woodhull Study Revisited, I sought to determine the extent to which the top 50 schools of nursing were using hashtags that could attract/invite attention from journalists on Twitter [11]. Preliminary findings using 2016-2018 data were intriguing but were not published with the rest of the results of The Woodhull Study Revisited [12]. In December 2020, the timeframe was expanded to encompass 2 more years of data so that before and after Woodhull Study Revisited analyses could be conducted. In addition, the scope was expanded to include an in-depth analysis of the types of hashtags used by schools of nursing. The resulting study is a comprehensive analysis of 4 years of tweets from the top 44 schools of nursing in the United States.

Methods have been described in detail using plain language so that researchers can easily replicate the study without needing specialized knowledge in natural language processing or machine learning. Democratizing Twitter analysis requires greater transparency regarding the methods used. As such, each table in this manuscript illustrates a step in the data analysis process that would otherwise be opaque to readers if the step was simply described in the narrative.

Methods

Research Question

The study sought to answer the following question: to what extent are top-ranked schools of nursing using hashtags that could attract/invite attention from journalists, policy makers, and the general public on Twitter? Below is a detailed description of the methods used for sampling, data collection, and data analysis.

Sampling

When this study began in February 2018, the sample of nursing schools was drawn from US News and World Report’s 2017 list of the top nursing schools with master’s degree programs. Fifty of the highest-ranked schools were selected from this list, with numerical rankings ranging from 1st to 48th (with several ties). The US News and World Report rankings were used as a mechanism for identifying the schools of nursing to include in this study with the knowledge that the rankings do not necessarily mean that the schools included at the top of the list are inherently “better” than the schools ranked lower. The decision to include the 50 highest-ranked schools of nursing in the sample was based on the fact that the US News and World Report rankings are the primary way that members of the media can quickly identify top schools of nursing nationally. The US News and World Report gets 7 million unique visitors to the education rankings and information webpages each month (US News and World Report, 2018).

In February 2018, of US News and World Report’s 50 top schools of nursing, two schools did not have a Twitter account and one school had a locked private Twitter account that was inaccessible to anyone other than those who were given permission by the school to follow the account. Thus, the school of nursing with the locked Twitter account and the two schools without a Twitter account were excluded from the 2016-2018 data set. The three schools omitted from the 2016-2018 data set are indicated in Table 1. In December 2020, when the second phase of this study was conducted, 44 of the original 47 schools of nursing still had public Twitter accounts under the same name used in the 2016-2018 data set. The three schools that no longer had a public Twitter account under the same name in 2020 are indicated in Table 1 and were omitted from both the 2016-2018 and 2018-2020 data sets for the sake of consistency.

Table 1.

Sample composition.

2017 US News & World Report Rank Name of the university Name of the school of nursing Official school Twitter account in February 2018 Account status in December 2020
#1 Duke University School of Nursing @DukeU_NrsngSchl Active
#2 Johns Hopkins University School of Nursing @JHUNursing Active
#3 University of Pennsylvania Penn Nursing Science @PennNursing Active
#4 Emory University Nell Hodgson Woodruff School of Nursing @EmoryNursing Active
#5 Ohio State University College of Nursing @osunursing Active
#6 Tie University of Washington School of Nursing @UWSoN Active
#6 Tie Yale University School of Nursing @YaleNursing Active
#8 Tiea Columbia University School of Nursing @CU_Nursing Inactive
#8 Tie University of Pittsburgh School of Nursing @UPittNursing Active
#10 University of Maryland–Baltimore School of Nursing @MarylandNursing Active
#11 Tie Case Western Reserve University Frances Payne Bolton School of Nursing @fpbnursing Active
#11 Tie University of Michigan–Ann Arbor School of Nursing @UMichNursing Active
#13 Tie New York University (Meyers) Rory Myers College of Nursing @NYUNursing Active
#13 Tie University of Alabama–Birmingham School of Nursing @UABSON Active
#15 Tie University of California Los Angeles School of Nursing @UCLANursing Active
#15 Tie Vanderbilt University School of Nursing @VanderbiltNurse Active
#17 University of North Carolina–Chapel Hill School of Nursing @UNCSON Active
#18 Rush University College of Nursing @RushUNursing Active
#19 University of Virginia School of Nursing @UVASON Active
#20 Tie Pennsylvania State University–University Park College of Nursing @PSUNursing Active
#20 Tie Rutgers University–Newark School of Nursing @RU_Nursing Active
#20 Tie University of Illinois–Chicago College of Nursing @UICnursing Active
#23 Tiea University of Iowa College of Nursing @UICollegeofNurs Inactive
#23 Tie University of Texas–Austin School of Nursing @LonghornNursing Active
#23 Tieb University of Texas Health Science Center–Houston Cizik School of Nursing No Twitter account found N/Ac
#26 Tieb Medical University of South Carolina College of Nursing @MUSC_CON
Locked account
N/A
#26 Tie University of Colorado Anschutz Medical Campus College of Nursing @NursingCU Active
#28 Tie Georgetown University School of Nursing and Health Studies @GtownNHS Active
#28 Tie Indiana University-Purdue University–Indianapolis School of Nursing @IUSONIndy Active
#28 Tieb University of San Diego Hahn School of Nursing and Health Science No Twitter account found N/A
#31 Tie Arizona State University College of Nursing and Health Innovation @asunursing Active
#31 Tie Boston College Connell School of Nursing @BC_CSON Active
#31 Tie The Catholic University of America School of Nursing @CUANursing Active
#31 Tie George Washington University School of Nursing @GWNursing Active
#31 Tie University of Utah College of Nursing @uofunursing Active
#36 Tie Oregon Health and Science University School of Nursing @OHSUNursing Active
#36 Tie University of Rochester School of Nursing @UofRSON Active
#38 Tie University of Cincinnati College of Nursing @UCnursing Active
#38 Tie University of Miami School of Nursing and Health Studies @UMiamiNursing Active
#38 Tie University of Missouri Sinclair School of Nursing @MizzouNursing Active
#41 Tiea University of Arizona College of Nursing @UACON Inactive
#41 Tie Washington State University College of Nursing @WSUNursing Active
#43 Tie University of Connecticut School of Nursing @UConnNursing Active
#43 Tie University of Missouri–Kansas City School of Nursing and Health Studies @UMKCSoNHS Active
#45 Tie Florida Atlantic University (Lynn) Christine E. Lynn College of Nursing @faunursing Active
#45 Tie University of Massachusetts–Amherst College of Nursing @UMAnursing Active
#48 Tie University of Alabama Capstone College of Nursing @uaccn Active
#48 Tie University of Tennessee–Knoxville College of Nursing @utknursing Active
#48 Tie Virginia Commonwealth University School of Nursing @VCUNursing Active
#48 Tie Wayne State University College of Nursing @WSUCoN Active

aSchools that no longer had a public Twitter account under the same name in 2020.

bSchools omitted from the 2016-2018 data set.

cN/A: not applicable.

Data Collection

Data collection was conducted twice during this study. In February 2018, a list of the top 50 schools of nursing was matched with publicly accessible Twitter accounts and then a data request was submitted to Export Tweet for the most recent 3200 tweets from each of the top-ranked schools of nursing. Because schools of nursing tweet with varying frequency, the past 3200 tweets for any given school of nursing covered a wide array of time frames. At one end of the spectrum, there were five schools of nursing, including Vanderbilt University, Johns Hopkins University, University of Michigan–Ann Arbor, Boston College, and University of Pennsylvania, for whom the oldest tweet in the data set was from 2016. At the other end of the spectrum, there were five schools of nursing, including University of Virginia, Yale University, Case Western Reserve University, University of Utah, and University of North Carolina–Chapel Hill, for whom the oldest tweet was from early 2009. Table 2 lists the oldest tweet in the data set from each school, with schools of nursing listed in order of their oldest tweet in the data set.

Table 2.

Oldest tweets in the 2016-2018 data set.

Name of the university Official school Twitter account Date of the oldest tweet in the 2016-2018 data set
University of Virginia @UVASON March 02, 2009
Yale University @YaleNursing March 10, 2009
Case Western Reserve University @fpbnursing March 12, 2009
University of Utah @uofunursing May 5, 2009
University of North Carolina–Chapel Hill @UNCSON May 7, 2009
University of California Los Angeles @UCLANursing August 7, 2009
New York University (Meyers) @NYUNursing October 27, 2009
University of Missouri–Kansas City @UMKCSoNHS December 07, 2009
University of Illinois–Chicago @UICnursing January 4, 2010
Arizona State University @asunursing January 19, 2010
Washington State University @WSUNursing January 29, 2010
Florida Atlantic University (Lynn) @faunursing April 22, 2010
University of Miami @UMiamiNursing April 30, 2010
George Washington University @GWNursing September 29, 2010
University of Alabama–Birmingham @UABSON May 12, 2011
Wayne State University @WSUCoN June 21, 2011
Indiana University-Purdue University–Indianapolis @IUSONIndy July 13, 2011
University of Washington @UWSoN July 26, 2011
Emory University @EmoryNursing February 10, 2012
Oregon Health and Science University @OHSUNursing February 18, 2012
Georgetown University @GtownNHS March 12, 2012
Ohio State University @osunursing April 12, 2012
University of Alabama @uaccn April 24, 2012
Duke University @DukeU_NrsngSchl May 11, 2012
University of Massachusetts–Amherst @UMAnursing June 12, 2012
University of Tennessee–Knoxville @utknursing July 17, 2012
Rush University @RushUNursing July 27, 2012
University of Maryland–Baltimore @MarylandNursing August 10, 2012
University of Missouri @MizzouNursing May 13, 2013
University of Rochester @UofRSON October 28, 2013
University of Colorado Anschutz Medical Campus @NursingCU February 28, 2014
University of Pittsburgh @UPittNursing March 18, 2014
Rutgers University–Newark @RU_Nursing April 30, 2014
University of Cincinnati @UCnursing June 17, 2014
Pennsylvania State University–University Park @PSUNursing October 23, 2014
University of Connecticut @UConnNursing November 30, 2014
Virginia Commonwealth University @VCUNursing January 27, 2015
University of Texas–Austin @LonghornNursing April 9, 2015
The Catholic University of America @CUANursing April 10, 2015
University of Pennsylvania @PennNursing March 24, 2016
Boston College @BC_CSON April 7, 2016
University of Michigan–Ann Arbor @UMichNursing June 16, 2016
Johns Hopkins University @JHUNursing July 22, 2016
Vanderbilt University @VanderbiltNurse September 29, 2016

Table 2 was used to determine the most recent “oldest tweet” date in the 2016-2018 data set. The @VanderbiltNurse Twitter account had the most recent “oldest tweet” (September 29, 2016), so September 29, 2016, was selected as the start date for the analysis. This meant that the time period to be covered in the 2016-2018 data set would be September 29, 2016, through February 22, 2018. Tweets with dates older than September 29, 2016, were filtered out from the data set, resulting in 16,939 tweets for the 2016-2018 data set. Table 3 describes the composition of the final 2016-2018 data set, with schools listed in alphabetical order by Twitter account name.

Table 3.

Composition of the 2016-2018 data set.

Name of the university Official school Twitter account Number of tweets
Arizona State University @asunursing 430
Boston College @BC_CSON 138
The Catholic University of America @CUANursing 7
Duke University @DukeU_NrsngSchl 415
Emory University @EmoryNursing 437
Florida Atlantic University (Lynn) @faunursing 303
Case Western Reserve University @fpbnursing 159
Georgetown University @GtownNHS 257
George Washington University @GWNursing 883
Indiana University-Purdue University–Indianapolis @IUSONIndy 251
Johns Hopkins University @JHUNursing 1992
University of Texas–Austin @LonghornNursing 545
University of Maryland–Baltimore @MarylandNursing 738
University of Missouri @MizzouNursing 49
University of Colorado Anschutz Medical Campus @NursingCU 206
New York University (Meyers) @NYUNursing 184
Oregon Health and Science University @OHSUNursing 312
Ohio State University @osunursing 949
University of Pennsylvania @PennNursing 1342
Pennsylvania State University–University Park @PSUNursing 94
Rutgers University–Newark @RU_Nursing 88
Rush University @RushUNursing 191
University of Alabama–Birmingham @UABSON 390
University of Alabama @uaccn 166
University of California–Los Angeles @UCLANursing 99
University of Cincinnati @UCnursing 318
University of Connecticut @UConnNursing 20
University of Illinois–Chicago @UICnursing 124
University of Massachusetts–Amherst @UMAnursing 38
University of Miami @UMiamiNursing 39
University of Michigan–Ann Arbor @UMichNursing 942
University of Missouri–Kansas City @UMKCSoNHS 31
University of North Carolina–Chapel Hill @UNCSON 80
University of Rochester @UofRSON 587
University of Utah @uofunursing 138
University of Pittsburgh @UPittNursing 179
University of Tennessee–Knoxville @utknursing 208
University of Virginia @UVASON 120
University of Washington @UWSoN 152
Vanderbilt University @VanderbiltNurse 2692
Virginia Commonwealth University @VCUNursing 107
Wayne State University @WSUCoN 42
Washington State University @WSUNursing 265
Yale University @YaleNursing 232

During phase two of the study, a data request was submitted to Vicinitas for all tweets from February 23, 2018, through December 13, 2020, from the 44 still-active Twitter accounts. Tweets prior to February 23, 2018, were deleted from the data set. Table 4 lists the oldest tweet in the 2018-2020 data set from each school, along with the number of tweets per school.

Table 4.

Oldest tweet and total tweets from each school in the 2018-2020 data set.

Name of the university Official school Twitter account Oldest tweet date Total number of tweets
University of Virginia @UVASON February 28, 2018 914
Yale University @YaleNursing February 23, 2018 550
Case Western Reserve University @fpbnursing February 23, 2018 701
University of Utah @uofunursing February 23, 2018 707
University of North Carolina–Chapel Hill @UNCSON February 23, 2018 396
University of California–Los Angeles @UCLANursing February 28, 2018 446
New York University (Meyers) @NYUNursing February 23, 2018 655
University of Missouri–Kansas City @UMKCSoNHS March 1, 2018 105
University of Illinois–Chicago @UICnursing February 27, 2018 523
Arizona State University @asunursing February 23, 2018 1943
Washington State University @WSUNursing February 23, 2018 504
Florida Atlantic University (Lynn) @faunursing February 23, 2018 565
University of Miami @UMiamiNursing February 27, 2018 445
George Washington University @GWNursing February 23, 2018 2056
University of Alabama–Birmingham @UABSON February 28, 2018 990
Wayne State University @WSUCoN February 27, 2018 141
Indiana University-Purdue University–Indianapolis @IUSONIndy February 25, 2018 445
University of Washington @UWSoN February 23, 2018 822
Emory University @EmoryNursing February 23, 2018 859
Oregon Health and Science University @OHSUNursing February 23, 2018 375
Georgetown University @GtownNHS February 23, 2018 961
Ohio State University @osunursing February 23, 2018 1927
University of Alabama @uaccn March 1, 2018 210
Duke University @DukeU_NrsngSchl February 23, 2018 900
University of Massachusetts–Amherst @UMAnursing April 27, 2018 53
University of Tennessee–Knoxville @utknursing February 23, 2018 577
Rush University @RushUNursing March 1, 2018 334
University of Maryland–Baltimore @MarylandNursing February 26, 2018 1348
University of Missouri @MizzouNursing February 26, 2018 258
University of Rochester @UofRSON February 23, 2018 558
University of Colorado Anschutz Medical Campus @NursingCU February 23, 2018 595
University of Pittsburgh @UPittNursing February 23, 2018 400
Rutgers University–Newark @RU_Nursing February 27, 2018 462
University of Cincinnati @UCnursing February 24, 2018 509
Pennsylvania State University–University Park @PSUNursing February 23, 2018 600
University of Connecticut @UConnNursing February 27, 2018 136
Virginia Commonwealth University @VCUNursing February 26, 2018 240
University of Texas–Austin @LonghornNursing February 25, 2018 795
The Catholic University of America @CUANursing March 9, 2018 1
University of Pennsylvania @PennNursing February 23, 2018 2357
Boston College @BC_CSON February 23, 2018 281
University of Michigan–Ann Arbor @UMichNursing February 23, 2018 1435
Johns Hopkins University @JHUNursing February 23, 2018 6570
Vanderbilt University @VanderbiltNurse February 23, 2018 4719

After cleaning the data, the 2016-2018 and 2018-2020 data sets were merged into a single data set containing 57,307 tweets. Table 5 describes the composition of the new 2016-2020 data set, with schools listed in alphabetical order by Twitter account name.

Table 5.

Composition of the final 2016-2020 data set.

Name of the university Official school Twitter account Number of tweets in the 2016-2018 data set Number of tweets in the 2018-2020 data set Total number of tweets in the 2016-2020 data set
Arizona State University @asunursing 430 1943 2373
Boston College @BC_CSON 138 281 419
The Catholic University of America @CUANursing 7 701 708
Duke University @DukeU_NrsngSchl 415 900 1315
Emory University @EmoryNursing 437 859 1296
Florida Atlantic University (Lynn) @faunursing 303 565 868
Case Western Reserve University @fpbnursing 159 2056 2215
Georgetown University @GtownNHS 257 961 1218
George Washington University @GWNursing 883 445 1328
Indiana University-Purdue University–Indianapolis @IUSONIndy 251 6570 6821
Johns Hopkins University @JHUNursing 1992 655 2647
University of Texas–Austin @LonghornNursing 545 1927 2472
University of Maryland–Baltimore @MarylandNursing 738 375 1113
University of Missouri @MizzouNursing 49 600 649
University of Colorado Anschutz Medical Campus @NursingCU 206 334 540
New York University (Meyers) @NYUNursing 184 462 646
Oregon Health and Science University @OHSUNursing 312 1 313
Ohio State University @osunursing 949 210 1159
University of Pennsylvania @PennNursing 1342 990 2332
Pennsylvania State University–University Park @PSUNursing 94 446 540
Rutgers University–Newark @RU_Nursing 88 509 597
Rush University @RushUNursing 191 595 786
University of Alabama–Birmingham @UABSON 390 136 526
University of Alabama @uaccn 166 523 689
University of California–Los Angeles @UCLANursing 99 1348 1447
University of Cincinnati @UCnursing 318 53 371
University of Connecticut @UConnNursing 20 445 465
University of Illinois–Chicago @UICnursing 124 1435 1559
University of Massachusetts–Amherst @UMAnursing 38 258 296
University of Miami @UMiamiNursing 39 105 144
University of Michigan–Ann Arbor @UMichNursing 942 396 1338
University of Missouri–Kansas City @UMKCSoNHS 31 2357 2388
University of North Carolina–Chapel Hill @UNCSON 80 400 480
University of Rochester @UofRSON 587 558 1145
University of Utah @uofunursing 138 577 715
University of Pittsburgh @UPittNursing 179 795 974
University of Tennessee–Knoxville @utknursing 208 707 915
University of Virginia @UVASON 120 914 1034
University of Washington @UWSoN 152 822 974
Vanderbilt University @VanderbiltNurse 2692 4719 7411
Virginia Commonwealth University @VCUNursing 107 240 347
Wayne State University @WSUCoN 42 504 546
Washington State University @WSUNursing 265 141 406
Yale University @YaleNursing 232 550 782

In December 2020, the original list of 47 schools of nursing was matched with publicly accessible Twitter accounts. Of the original 47 schools of nursing, 44 still had public Twitter accounts under the same name used in the first part of the study. The three Twitter accounts that were no longer active (@UICollegeofNurs, @UACON, and @CU_Nursing) were removed from the original data set, resulting in a data set containing 16,939 tweets from 44 top-ranked schools of nursing. The most recent 3200 tweets from each of the Twitter accounts were extracted and analyzed. Excluding retweets, there were 40,368 tweets for the time period covered (February 23, 2018, through December 13, 2020). These 40,368 tweets were added to the data set, resulting in a data set containing 57,307 tweets from September 29, 2016, through December 13, 2020.

Data Analysis

The analyses in this study were conducted using R version 4.0.3 (Bunny-Wunnies Freak Out), R Studio Version 1.3.1093, and Microsoft Excel for Mac Version 16.43. The following are the steps taken to generate a list of the most frequently used hashtags in the 2016-2020 data set, along with the number of times each hashtag appeared. Initially, the Excel file was uploaded to R software. The R Markdown package was installed, and the elements of Van Horn and Beveridge coding were used [13]. The text strings in the data set were cleaned. The character encoding in tweets was homogenized to remove the strings of nonsense characters indicating the presence of emojis in the source tweets. This converted character encoding to Unicode UTF-8. Thereafter, capitalization in tweets was removed by turning everything into lowercase. Subsequently, extra whitespace and URLs were removed from the tweets. Once the text strings were cleaned, the hashtags present in the data set were identified and a list of the hashtags from most to least frequently used was generated. The data frame generated in R was exported to Excel, with hashtags listed in one column and their frequency in another. The corresponding script in R has been provided in Multimedia Appendix 1 so that readers can replicate the analysis.

Because there was interest in detecting changes in the use of hashtags by schools of nursing after the results of The Woodhull Study Revisited were published in Fall 2018, the steps described above were repeated to split the 2016-2018 data set into two parts. The first covered September 29, 2016, through September 27, 2018 (the day that The Woodhull Study Revisited was published in the Journal of Nursing Scholarship), and the second covered September 28, 2018, through December 13, 2020. The same process outlined previously was used to analyze the data and generate frequency tables for the hashtags used during each time period of interest.

Results

There were 6866 different hashtags used in the 2016-2020 data set. All hashtags that had been used 100 times or more across the entire corpus of tweets in the data set were identified, and these 71 hashtags were characterized as being those with the highest frequency of use by the schools of nursing in the study. These 71 hashtags were used a total of 26,243 times in the 2016-2020 data set, as detailed in Table 6. Among the 6866 different hashtags appearing in the 2016-2020 data set, 3774 were used only once and 6178 were used 10 or fewer times.

Table 6.

Hashtags used 100 times or more in the 2016-2020 data set.

Hashtag Number of times used
#nursing 3259
#pennnursing 1980
#healthcare 1265
#gwu 1192
#nurses 991
#covid19 895
#umson 887
#nurse 857
#jhson 606
#conhi 587
#nursingschool 565
#dnp 535
#vandygram 452
#nursesweek 451
#emorynursing 444
#bsn 442
#canenurse 419
#uabson 374
#npslead 372
#msn 358
#umichnursing 353
#tbt 348
#pennnursinginnovation 347
#volnurse 335
#simulation 287
#fpbnursing 279
#phd 260
#runursing 247
#gocougs 245
#raisehigh 232
#research 230
#icymi 226
#np 218
#cunursing 215
#vusn 215
#health 210
#hiv 205
#mentalhealth 204
#buckeyenurses 200
#nursepractitioner 199
#virginia 196
#yearofthenurse 185
#wegotthis 173
#veterans 170
#buckeyenurse 169
#nashville 164
#gohopnurse 161
#fau 160
#innovation 156
#amrchat 154
#uic 150
#npweek 149
#icowhi16 144
#jhuson 143
#givingtuesday 141
#meninnursing 136
#cwru 132
#huskynurses 132
#prerequisites 125
#globalhealth 122
#ahcj19 118
#bestgradschools 115
#nyu 115
#huskynurse 112
#opioid 111
#nursingstudent 109
#nurseleader 107
#nursingresearch 103
#nationalnursesweek 102
#umich 102
#uofunursing 101

When the data set was divided into two parts to detect changes in the use of hashtags by schools of nursing after the results of The Woodhull Study Revisited were published, the findings were similar to those of the analysis of the data set as a whole. There were 27 hashtags that had been used 100 times or more in the September 29, 2016, to September 27, 2018, data set. Among the 3307 different hashtags appearing in this data set, 1806 (54.6%) were used only once and 3028 (91.6%) were used 10 or fewer times. In comparison, there were 47 hashtags that had been used 100 times or more in the September 28, 2018, to December 13, 2020, data set. Among the 4812 different hashtags appearing in this data set, 2716 (56.4%) were used only once and 4350 (90.4%) were used 10 or fewer times. Tables 7 and 8 provide details on the hashtags used 100 times or more during each time period.

Table 7.

Hashtags used 100 times or more before The Woodhull Study Revisited.

Top hashtags (September 29, 2016-September 27, 2018) Number of times used
#nursing 1671
#pennnursing 1017
#gwu 671
#umson 530
#healthcare 516
#nurses 507
#nurse 409
#jhson 402
#conhi 393
#emorynursing 252
#nursingschool 243
#bsn 232
#nursesweek 227
#tbt 205
#buckeyenurses 177
#dnp 164
#volnurse 156
#amrchat 154
#icowhi16 144
#jhuson 143
#research 136
#buckeyenurse 133
#health 128
#canenurse 111
#wegotthis 109
#cunursing 106
#virginia 104

Table 8.

Hashtags used 100 times or more after The Woodhull Study Revisited.

Top hashtags (September 28, 2018-December 13, 2020) Number of times used
#nursing 1588
#pennnursing 963
#covid19 895
#healthcare 749
#gwu 521
#nurses 483
#vandygram 449
#nurse 448
#dnp 371
#umson 357
#umichnursing 353
#npslead 350
#nursingschool 322
#uabson 313
#canenurse 308
#msn 275
#pennnursinginnovation 264
#simulation 229
#raisehigh 228
#nursesweek 224
#bsn 210
#phd 205
#jhson 204
#conhi 194
#emorynursing 192
#yearofthenurse 185
#fpbnursing 182
#volnurse 179
#runursing 177
#vusn 171
#gocougs 163
#gohopnurse 161
#nashville 161
#mentalhealth 151
#tbt 143
#np 141
#fau 132
#icymi 129
#nursepractitioner 128
#meninnursing 127
#ahcj19 118
#hiv 115
#npweek 112
#cunursing 109
#cwru 104
#veterans 102
#uofunursing 101

Typology of Frequently Used Hashtags

Using Excel, a thematic analysis was conducted of the hashtags that were used 100 times or more in the 2016-2020 data set. Collectively, the 71 hashtags were used a total of 26,243 times. To conduct the thematic analysis, the list of 71 frequently used hashtags was considered and similarities were assessed. As similarities were identified, the hashtags were grouped into categories, and this process of coding (and recoding) hashtags was continued until there were six categories that explained the vast majority of the hashtags. A seventh category was added to capture the assortment of hashtags that did not lend themselves to categorization. The following seven types of hashtags emerged during the process of thematic analysis: (1) Nursing, hashtags about nurses, nursing, nursing degrees, nursing licenses, etc; (2) Schools, hashtags about universities, schools, colleges, mascots, or locations; (3) Illness/disease/condition, hashtags about illnesses, diseases, conditions, or awareness day/month; (4) Population, hashtags about populations that nurses serve; (5) Health, hashtags about health care, health, global health, etc; (6) Conference or tweet chat, hashtags about conferences or specific Twitter chats for health care professionals; (7) Something else, hashtags that did not fit into one of the other six categories. Table 9 lists the hashtags contained in each of the seven categories.

Table 9.

Hashtag typology of the 2016-2020 data set.

Category Description of the category Hashtags Number of times used
Nursing About nurses, nursing, nursing degrees, nursing licenses, etc #bsn, #dnp, #meninnursing, #msn, #nationalnursesweek, #np, #npslead, #npweek, #nurse, #nurseleader, #nursepractitioner, #nurses, #nursesweek, #nursing, #nursingresearch, #nursingschool, #nursingstudent, #phd, #prerequisites, #simulation, and #yearofthenurse 9810
Schools About universities, schools, colleges, mascots, or locations #bestgradschools, #buckeyenurse, #buckeyenurses, #canenurse, #cunursing, #cwru, #emorynursing, #fau, #fpbnursing, #gocougs, #gohopnurse, #gwu, #huskynurse, #huskynurses, #jhson, #jhuson, #nashville, #nyu, #pennnursing, #pennnursinginnovation, #raisehigh, #runursing, #uabson, #uic, #umich, #umichnursing, #umson, #uofunursing, #vandygram, #virginia, #volnurse, and #vusn 10,974
Illness/disease/condition About illnesses, diseases, conditions, or awareness day/month #covid19, #hiv, and #opioid 1211
Population About populations that nurses serve #veterans 170
Health About health care, health, global health, etc #globalhealth, #health, #healthcare, and #mentalhealth 1801
Conference or tweet chat About conferences or specific Twitter chats for health care professionals #ahcj19, #amrchat, #conhi, and #icowhi16 1003
Something else Hashtags that did not fit into one of the other six categories #givingtuesday, #icymi, #innovation, #research, #tbt, and #wegotthis 1274

For the purposes of this study, the seven types of hashtags were considered to be either inward facing (“intercom hashtags”) or outward facing (“megaphone hashtags”). Intercom hashtags were those intended to invite attention from/interaction with nurses, members of the university/school community, or attendees at a nursing conference or Twitter chat. Megaphone hashtags were those intended to invite attention from/interaction with people such as journalists, policymakers, and the general public.

The intercom hashtag types were as follows: nursing (hashtags about nurses, nursing, nursing degrees, nursing licenses, etc); schools (hashtags about universities, schools, colleges, mascots, or locations); and conference or tweet chat (hashtags about conferences or specific Twitter chats for health care professionals). The megaphone hashtag types were as follows: illness/disease/condition (hashtags about illnesses, diseases, conditions, or awareness day/month); population (hashtags about populations that nurses serve); health (hashtags about health care, health, global health, etc); and something else (hashtags that did not fit into one of the other six categories).

The vast majority of the 71 hashtags that were used 100 times or more in the 2016-2020 data set can be categorized as intercom hashtags (inward-facing hashtags focused on in-group discussion within and about the profession). Collectively, nursing hashtags (n=9810, 37.4%), school hashtags (n=10,974, 41.8%), and conference or tweet chat hashtags (n=1003, 3.8%) comprised 83.0% (n=21,787) of the 26,243 times that the 71 frequently used hashtags occurred in the data set.

In contrast, few of the 71 hashtags that were used 100 times or more in the 2016-2020 data set can be categorized as megaphone hashtags. Collectively, health hashtags (n=1801, 6.9%), illness/disease/condition hashtags (n=1211, 4.6%), and population hashtags (n=170, 0.7%) comprised 12.1% (n=3182) of the 26,243 times that the 71 frequently used hashtags occurred in the data set. When the “something else” hashtags (5%) were added, the total of megaphone hashtags was approximately 18% of the 26,243 times that the 71 frequently used hashtags occurred in the data set.

When the data set was divided into two parts to detect changes in the use of hashtags by schools of nursing after the results of The Woodhull Study Revisited were published, the findings were similar to those of the analysis of the data set as a whole, with one notable exception. Prior to the publication of The Woodhull Study Revisited on September 27, 2018, none of the hashtags that were used 100 times or more pertained to an illness, disease, or condition. In the 2 years after the publication of The Woodhull Study Revisited, 7% of the frequently used hashtags pertained to an illness, disease, or condition. Further analysis revealed that this shift was attributable to the use of the following two hashtags: #covid19 (n=895) and #hiv (n=115).

Missed Opportunities for Tweeting About Trending Topics

Of the 6866 different hashtags appearing in the 2016-2020 data set, 6178 were used 10 times or less. These seldom-used hashtags included a number of hashtags that were widely used on Twitter during the time period covered by this study. Table 10 contains a list of some of these hashtags along with the number of times each hashtag was used in the 2016-2020 data set.

Table 10.

Missed opportunities to use hashtags of public interest.

Topic and hashtag Number of times used in the 2016-2020 data set
Racism, racial bias, and racial justice

#racism 10

#blacklivesmatter 9

#antiracism 6

#blm 6

#bias 3

#implicitbias 1

#racialbias 1

#unconsciousbias 1

#systemicracism 1

#racialjustice 1
Sexism, sexual harassment, and rape

#sexualharassment 2

#rape 2

#sexism 1

#timesuphealthcare 1
Politics

#electionday 9

#vote 8

#election2020 2

#election 2

#trump 2

#election2016 1

#presidentialdebate2020 1
LGBTQa+ health

#lgbtqhealth 2

#homophobia 1

#heterosexism 1

#transhealth 1
Cancer

#lungcancer 8

#pancreaticcancer 3

#colorectalcancer 3

#ovariancancer 2

#skincancer 1

#pediatriccancer 1

#livercancer 1

#childhoodcancer 1
Other diseases and conditions

#kidneydisease 6

#hepatitis 2

#arthritis 2

#hearingloss 2

#parkinsons 1

#als 1
Sexual health

#sexualhealth 7

#sexuality 1

#abortion 1

#condom 0

#birthcontrol 0

#familyplanning 0
End of life

#death 6

#grief 2

#advancedirective 1

#livingwill 1

#dying 0

aLGBTQ: lesbian, gay, bisexual, transgender, gender non-conforming, queer and/or questioning.

Discussion

Although the top 44 schools of nursing have an active social media presence on Twitter, collectively, their use of hashtags functions more like an intercom to communicate with other nurses rather than a megaphone to invite attention from and dialogue with journalists, policy makers, and the general public. Because intercom hashtags are both inward facing and overused, they are of minimal use when it comes to drawing attention from and interacting with people outside of nursing. If schools of nursing want the media to showcase the voices of their faculty members as experts, schools of nursing need to be more strategic in their use of hashtags on Twitter. In order to accomplish this, schools of nursing need to increase their use of megaphone hashtags to connect the work of their faculty and students with topics and events of interest to the general public. For example, when topics like #guncontrol are trending, schools of nursing could tweet about the work their faculty members are doing in violence prevention.

On Twitter, schools of nursing have a unique opportunity to amplify the voices of their faculty members on health-related topics of widespread public interest like the impact of systemic racism on health, gun violence, and access to care, among others. If schools of nursing continue to use mostly intercom hashtags on Twitter, they will have squandered a powerful opportunity to share their expertise beyond the boundaries of the discipline.

Acknowledgments

I thank the following individuals: Curtis Kephart, who manages the @RStudio Twitter account, for replying to my tweet with advice about using case_when inside dylyr::mutate; John D Martin, III for responding to my tweet and then following up with a proposed script on RStudio Community when I was working on a streamgraph for this project; Martin Wade for answering my question on RStudio Community with a proposed script for creating a streamgraph; Dan Sullivan for his response to my post on RStudio Community, his explanation on how to create a reprex, and his reprex for the problem I was trying to solve; Barbara Glickstein and Diana Mason for inviting me to conduct the first part of this project as a last-minute addition to The Woodhull Study Revisited; Mary Jean Schumann for her support of the study when she was head of the George Washington University School of Nursing’s Center for Health Policy and Media Engagement; and Timothy Keyes for writing a script snippet for me and sharing it on GitHub when I was struggling to create a data frame in R. The September 29, 2016, to February 22, 2018, Twitter data for this project were purchased by the George Washington University School of Nursing’s Center for Health Policy and Media Engagement for $1000 with funds received from the Gordon and Betty Moore Foundation, Robert Wood Johnson Foundation, Beatrice Renfield Foundation, Sigma Theta Tau International, American Association of Critical-Care Nurses, Donald and Barbara Jonas Foundation, National League for Nursing, OnCourse Learning, American Association of Colleges of Nursing, American Organization of Nurse Executives, and Wolters Kluwer Health. No funding was provided for this study beyond the $1000 used for the purchase of data. The February 23, 2018, to December 13, 2020, Twitter data for this project were purchased with my personal funds (US $40).

Appendix

Multimedia Appendix 1

R script for generating the data frame of the most frequently used hashtags in the data set.

Footnotes

Conflicts of Interest: None declared.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Multimedia Appendix 1

R script for generating the data frame of the most frequently used hashtags in the data set.


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