`

YouTube Videos Produced by U.S. Public Libraries:
Analysing Popularity and Factors that Increase
Views
Yuhiro Mizunuma1, Kazuki Sato1, Fumiaki Miyazaki1, Keita Tsuji2
1 Faculty of Media and Information Resources, Surugadai University, Japan
2 Faculty of Library, Information and Media Science, University of Tsukuba, Japan

Abstract: Public libraries are increasingly posting content on social media platforms
such as Facebook, Twitter, and YouTube. In this paper, we focus on YouTube videos
produced by U.S. public libraries and identify the factors that increase their views.
Specifically, we compared 107 popular videos (with over 700 views) and 109 unpopular
ones (with less than 12 views) and analysed their differences. This research revealed thatthe unpopular videos were often too short (less than 10 seconds) or too long (more than
20 minutes). The popular videos overall were more informative than unpopular ones(e.g. with longer titles to identify the contents of the videos). Furthermore, the ratios oftutorials and story times for popular videos (28.0% and 21.5%, respectively) weresignificantly higher than those for unpopular ones (6.4% and 10.1%, respectively). The
ratios of reports on events and event notices among popular videos (7.5% and 12.1%,
respectively) were significantly lower than those for unpopular ones (26.6% and 25.7%,
respectively).
Keywords: YouTube; Public Libraries; Library Marketing; Library Services

1. Introduction
Many public libraries are now posting content on such social media platforms
as Facebook, Twitter, and YouTube. As will be discussed in Section 2 below,
many studies have been conducted regarding libraries’ uses of Facebook andTwitter. However, there have been very few studies on libraries’ employment
of YouTube. In this paper, we focus on YouTube videos produced by U.S.
public libraries and examine the factors that helped to increase their views.
First, we examined how many U.S. public libraries used each major form ofsocial media, including YouTube, based on information from their official
websites. We then developed a list of libraries posting YouTube videos andselected 109 unpopular videos (those having fewer than 12 views) and 107
popular videos (those having over 700 views). We compared popular andunpopular videos with a focus on the videos’ (1) time lengths, (2) titles, (3)descriptions, (4) uses of voice (i.e., whether or not the videos featured voices),(5) contents, and (6) cast members. This research presents a real-world pictureof libraries’ YouTube use and should be helpful to libraries want to increase
views of their YouTube videos and better serve the public.

2. Related Studies
Many studies have been conducted regarding libraries’ use of Facebook andTwitter. For example, Vassilakaki and Garoufallou (2014) conducted literature
review on libraries’ uses of Facebook, analysing 50 papers published between
2006 and 2012. They found that main body of the relevant literature focused onreporting experiences, problems, and lessons learned from building a presence

on Facebook. Vassilakaki and Garoufallou (2015) also conducted a literature
review of libraries uses of Twitter. They conducted database retrieval using LIS
databases with research phrases such as ‘Twitter and libraries’ or ‘Twitter andlibrarians’, and 630 papers were identified. Based on the review of 51 papers,
they found that the papers mainly presented the reasons behind the adoption of
Twitter and how it is used specifically to meet the various needs and purposesof libraries. Some research clarified the actual use of Facebook and Twitter
based on data posted from libraries. For example, Aharony (2012) conducted an
exploratory analysis of Facebook pages developed by 20 American public andacademic libraries to understand patterns of libraries’ Facebook use. Aharony(2010) also analysed tweets posted by 30 public and academic libraries andconducted statistical descriptive analysis and content analysis. Yoshida (2014)
and Ishikka et al. (2012) also conducted similar analyses of public andacademic libraries in Japan.
On the other hand, usage trends on YouTube were examined with the othersocial media platforms. For example, Taylor & Francis (2014) conducted asurvey on libraries’ use of social media, including YouTube. The survey foundthat more than 70% of libraries were using social media tools, 60% had a social
media account for three years or longer, and 30% of librarians were posting atleast once per day. It also found that Facebook and Twitter remained the mostpopular platforms, but there was a particular acceleration of interest in visual
platforms such as YouTube, Pinterest, and Snapchat. Moreover, the survey
showed that social media platforms including YouTube were increasingly
considered collection management tools, offering flexible ways to present
resources such as digital video collections.
Although they are fewer in number than studies focused on libraries’
Facebook and Twitter use, there are some studies that have examined libraries’
uses of YouTube. Webb (2007) discussed the effectiveness of libraries’
YouTube use. Ariew (2009), Intahchomphoo (2013), and Cho (2013) discussed
the possibilities and problems with libraries’ YouTube use based on theexamples of the University of South Florida, University of Ottawa’s Brian
Dickson Law Library, Harvard Law School Library, and the libraries of the
University of British Columbia, respectively. Colburn and Haines (2012)
examined libraries’ YouTube use in detail to understand how libraries employ
YouTube for outreach. To select sample videos, they searched YouTube withfour keywords (library, libraries, librarian, and librarians), categorized 373
videos, retrieved 55 videos that were created by libraries for promotional
purposes, and analysed those videos in detail with a focus on content: thewebsites linked to the videos, interactive features such as comments, and views.
Colburn and Haines found that the ‘general promotion/appreciation’ of libraries
was the most common type of library promotional material created on the sites.
Their research also found that from 2008 to 2009, view counts grew by 174 percent on average.
Our study also focuses on YouTube use in libraries. In addition, in light of
Aharony (2012, 2014) and Colburn and Haines (2012), we have adopted anempirical approach to relevant social media content produced by libraries.
However, unlike previous research, we aimed to identify the factors that
increased view counts. To this end, we focused on YouTube videos produced
by U.S. public libraries, comparing 107 popular videos (having over 700 views)
and 109 unpopular ones (having fewer than 12 views), and examined theirdifferences. To our knowledge, this is the first such study to identify the factorsthat increase libraries’ views on YouTube .

3. MethodWe first examined how many U.S. public libraries used YouTube. In addition,
based on the collected data, we determined the elements that increased theirview counts. In this section, we will explain each method.
3.1 Method of Investigation for Libraries’ Utilization of YouTube
We first determined how many U.S. public libraries used YouTube. We
examined not only YouTube but also other social media platforms, such as
Facebook, in order to view the use of YouTube in more detail.
For background, we investigated libraries’ official websites. If there were
notices or links to social media on a library’s website, we assumed the library
was engaged with social media. Data from official websites were obtained from
American Library Directory (http://www.americanlibrarydirectory.com/),
published by Information Today. It includes profiles of approximately 36,000
public, academic, special, and government libraries and library-relatedorganizations in the U.S. and Canada—including website URLs. We assumed
the URLs to be for the official websites, and we conducted the survey based on
those URLs. We selected the sample libraries and URLs according to thefollowing steps:(1) We downloaded records of 9,629 U.S. public libraries (only main libraries)
using American Library Directory. More specifically, we conductedadvanced searches using research options shown in Figure 1.

Figure 1. Search Condition1(2) We randomly chose 1,000 library records from the 9,629 library records.
(3) We excluded 157 libraries that had no website URL data (843 libraryrecords remained).

(4) We excluded 112 libraries with websites that we could not reach for suchreasons as broken links (731 library records remained).
Next, we investigated how social media platforms, including YouTube, wereused in 731 public libraries. The platforms we considered included (1)YouTube, (2) Facebook, (3) Twitter, (4) Instagram, (5) Pinterest, (6) Flickr, (7)Tumblr, (8) LinkedIn, (9) Goodreads, and (10) SoundCloud. As mentioned
above, if there were advertisements or links to social media on a library’s
official website, we assumed the library used social media.
We also determined the details of the accounts and links. Morespecifically, we classified the accounts and links based on the following
conditions: (1) The library had its own account; (2) the library did not have its
own account, but it had the respective municipality’s account and posted
library’s information; (3) the library did not have its own account but had themunicipality’s account, and it had not posted library’s information; (4) the
website had a notice or icon for social media but no link to the social media
platform; (5) the website had a notice or icon for social media, but the link was
broken; (6) the website had a notice or icon for social media, but we could notview the account for such reasons as location restriction. We conducted thissurvey from 8 September to 12 September 2018.
3.2 Method for Investigating the Factors that Increase Social Media Views
Based on the data collected regarding libraries’ utilization of YouTube, weinvestigated the elements that increase their views. More specifically, we
compared libraries’ popular YouTube videos with unpopular ones andidentified their differences. We used 107 popular videos and 109 unpopular
videos as our sample. Videos were selected based on the following factors:(1) The 96 libraries investigated in the previous section possessed their own
YouTube accounts. The number of unique accounts was 932. We excluded
one account that could no longer be found3. We also excluded 27 accounts
that posted more than 50 videos4.
(2) We defined popular videos as those with over 700 views. The sample of
popular videos included 107 videos.
(3) We defined unpopular videos as those with less than 12 views and with agap of six months since uploading5. The sample of unpopular videos
included 109 videos.
We compared the 107 popular and 109 unpopular videos, consideringcharacteristics shown in Table 1. For example, we compared popular andunpopular videos, focusing on the video’s length, and attempted to determine
the factors that increased views. The ‘Contents’ section in Table 1 highlights
classifications based on videos’ contents, and it will be explained in more detailin the next section. The race of the video cast members was estimated based ona face recognition web service, Betaface (https://betaface.com/demo_old.html),
using a screenshot from each video. We conducted this survey from 24
September 2018 to 1 April 2019.

Table 1. Investigation Items
Time

Video Length (hh:mm:ss)

Title

Length of the title (Number of the characters and words)
The words in the title

Descriptions

Whether the video included written descriptions

Voice

Whether the video had voice sounds or not
Language of the video (English or Spanish)

Contents

Contents of the video

Cast members Whether the video had a cast
Number of cast members
Race of the cast members
Roles of the Cast

4. Results
In this section, we first show the results of the investigation into libraries’ usesof YouTube. Afterward, we will show the results concerning our investigationof the factors that increase views. The results are shown in terms of time, title,
descriptions, voices, contents, and cast members in this order.
4.1 Results Concerning Libraries’ Utilization of YouTube
Table 2 through Table 6 show the utilization ratios of each social media
experience, and classifications (a) to (f) represent whether (a) the library had its
own account; (b) the library did not have its own account, but it had themunicipality’s account on which it posted library information; (c) the library
did not have its own account and had its municipality’s account, but it had notposted library’s information; (d) there was an advertisement or icon for social
media on the website but no link to the social media account; (e) there was anadvertisement or icon for social media on the website, but the link was broken;
and (f) there was an advertisement or icon for social media, but we could notview the account for such reasons as location or privacy restriction.
The numbers in parentheses in Table 2 represent the number of libraries
investigated. For example, concerning YouTube, 92 libraries have libraryaccounts, and this comprises 12.6% of our sample libraries (731 libraries).
Facebook’s utilization ratio was higher than any other social media’s ratio.
Concerning the ‘(a) ratio of library account’, the utilization ratio of YouTube(12.6%) was the fifth highest in our sample of social media, following
Facebook (69.5%), Twitter (31.6%), Instagram (20.9%), and Pinterest (14.8%).
Almost all sample social media contained broken links; this study shows thatmaintenance of links is an issue for libraries.
Table 2. Utilization Ratios of Social Media Platforms (1)YouTube

Facebook(a) Libraries' account

12.6% ( 92 )

69.5% ( 508 )(b) Municipalities' account with library post

0.7% (

5 )

0.1% (1 )(c) Municipalities' account with no library post

1.9% ( 14 )

2.2% (

16 )(d) No link

0.0% (

0 )0.1% (

1 )(e) Broken link

0.7% (

5 )

2.6% (

19 )(f) We cannot view

0.0% (

0 )1.9% (

14 )n = 731

Table 3. Utilization Ratios of Social Media Platforms (2)Twittern = 731

Instagram(a) Libraries' account

31.6% ( 231 )

20.9% ( 153 )(b) Municipalities' account with library post

0.5% (

4 )0.0% (0 )(c) Municipalities' account with no library post

2.1% ( 15 )

0.7% (

5 )(d) No link

0.0% (

0 )0.0% (0 )(e) Broken link

2.6% ( 19 )

1.4% (

10 )(f) We cannot view

0.0% (

0.0% (0 )0 )Table 4. Utilization Ratios of Social Media Platforms (3)Pinterestn = 731

Flickr(a) Libraries' account

14.8% ( 108 )

4.9% (36 )(b) Municipalities' account with library post

0.0% (

0 )0.0% (0 )(c) Municipalities' account with no library post

0.0% (

0 )0.1% (

1 )(d) No link

0.0% (

0 )0.0% (0 )(e) Broken link

0.8% (

6 )0.0% (

0 )(f) We cannot view

0.0% (

0 )0.0% (

0 )Table 5. Utilization Ratios of Social Media Platforms (4)Tumblrn = 731

LinkedIn(a) Libraries' account

1.5% ( 11 )1.4% (10 )(b) Municipalities' account with library post

0.0% (

0 )0.1% (1 )(c) Municipalities' account with no library post

0.0% (

0 )0.4% (

3 )(d) No link

0.0% (

0 )0.0% (0 )(e) Broken link

0.1% (

1 )

0.1% (

1 )(f) We cannot view

0.0% (

0 )0.0% (

0 )Table 6. Utilization Ratios of Social Media Platforms (5)n = 731

Goodreads

SoundCloud(a) Libraries' account

1.1% (

8 )

0.8% (6 )(b) Municipalities' account with library post

0.0% (

0 )0.0% (0 )(c) Municipalities' account with no library post

0.0% (

0 )0.0% (

0 )(d) No link

0.0% (

0 )0.0% (0 )(e) Broken link

0.4% (

3 )0.0% (

0 )(f) We cannot view

0.0% (

0 )0.0% (

0 )4.2 Results Concerning Time
Table 7 represents the length of the videos in terms of the mean (average),
median, maximum, and minimum times. The mean for popular videos was 3
minutes, 44 seconds and the mean for unpopular videos was 4 minute 29
seconds. There was no significant difference between popular and unpopular
videos based on Welch’s t-test at 0.05 levels. Table 7 further shows that the
maximum length of unpopular videos (one hour 23 minutes 18 seconds) was
longer than that of popular videos (19 minutes 41 seconds), whereas theminimum length of unpopular videos (3 seconds) was shorter than that of
popular videos (29 seconds). In addition, there were 19 videos in which thelengths of time were longer than 20 minutes or shorter than 30 seconds for all(i.e., popular and unpopular) videos. Remarkably, only one of them was a
popular video, and the rest (18 videos) were unpopular ones.
Table 7. Video Length (hh:mm:ss)
Popular

Unpopular(n=107)(n=109)Mean

0:03:44

0:04:29Median0:02:52

0:02:01

Maximum

0:19:41

1:23:18

Minimum

0:00:29

0:00:03

4.3 Results Comparing Video Titles
Tables 8 and 9 show the results of the length of each video’s title. Table 8shows the mean, median, maximum, and minimum of the number of charactersin the title. Table 9 shows the number of words in the title. The asterisks in the‘Mean’ column represent significant differences based on Welch’s test. Single
asterisks indicate that there was significance at the 0.05 level; double asterisks
indicate significant differences at the 0.01 level. Concerning both the number ofcharacters and the number of words, the mean and median of popular videos
were higher than unpopular videos, and there were significant differences
between popular and unpopular videos.
Table 10 shows the frequency of certain words in the titles. We calculated
frequencies of the words, and the top 10 words are presented in Table 10. The
numbers in parenthesis represent words’ frequencies. ‘Library’ appeared withthe highest frequency in both popular and unpopular videos. In this table,findings show that, unlike unpopular videos, popular videos included ‘tutorial’,and terms related to eBooks such as ‘eBooks’, ‘OverDrive’, and ‘downloading’.

On the other hand, unlike popular videos, unpopular videos included words that
may be related to library records such as ‘Vlog’, ‘2017’, and ‘2013’.
Table 8. Length of Video Title (The Number of Characters)
Popular
Unpopular(n=107)(n=109)Mean

38.74 **

30.94

Median38

28

Maximum

80

82

Minimum

8

8

Table 9. Length of Video Title (The Number of Words)
Popular
Mean

Unpopular(n=107)(n=109)6.25 **

5.21

Median6

5

Maximum

14

13

Minimum

1

1

Table 10. The Top Ten Words in the Title
Popular

Unpopular

1library (42)library (24)2the (32)

the (16)3

public (15)display (13)4OverDrive (14)

CBPL, Vlog (12)5

for (13)time (10)6

your, to (12)FPLDs, toddler, is , for (9)7and (11)2017, 2013 (8)8downloading (9)of, a, with (7)9with (8)book, reading, at, summer, 2 (6)10tutorial, eBooks, episode (7)interview, public, celebration, 1, 01 (5)4.4 Results Concerning Descriptions
Table 11 provides the ratios of the videos that included descriptions. The tableshows that 95.3% of popular videos had descriptions, whereas only 78.0% of
unpopular videos included descriptions. The research found significant
differences in the ratio between popular videos and unpopular videos, based on
the Z-test for proportions at the 0.01 levels.

Table 11. The Ratios of Videos Including Descriptions
Popular
Unpopular(n=107)
95.3% **

(n=109)78.0%

4.5 Results Concerning Voice
Table 12 shows the ratios of the videos that had voice sounds. Table 12 showsthat 86.9% of popular videos included vocal sounds, or voices, whereas 74.3%
of unpopular videos included voices. There were significant differences
between the ratios among popular videos and unpopular videos based on the Ztest for proportions at 0.05 levels.
Interestingly, among popular videos, Spanish was spoken in three videos,and sign language was used in one video. There was no such video among
unpopular videos.

Table 12. The Ratios of the Video Including Voice Sounds
Popular
Unpopular(n=107)
86.9% *

(n=109)74.3%

4.6 Results Concerning Contents
Table 13 displays the results of our content analysis. The findings show thatsome libraries provided library services through YouTube and others used
YouTube to introduce or promote their libraries. Library services provided
through YouTube included the introduction of materials such as books or CDs,and it included tutorials and story times. Typical tutorials included those forknitting, cord cutting, installing eBooks, and playing a board game. Whenlibraries offered introductions to the library, they typically included general
introductions of promotional videos, services, events, buildings, and displays.
There were entertainment videos, comedies, or videos to build familiarity. The‘Others’ category includes ‘August Storm’ videos, for example, featuring
recordings of thunderstorms pushing recycling bins around the library’s parking
lot. ‘Unknowns’ were videos for which we could not understand the purpose.
Table 13 shows that there were significant differences between popular andunpopular videos in terms of content. The ratios of popular videos weresignificantly higher than those of unpopular videos concerning tutorials (28.0%
and 6.4%, respectively), story times (21.5% and 10.1%, respectively),
introductions of services (26.2% and 6.4%, respectively), and entertainments,
comedies, or videos to build familiarity (14.0% and 0.0%, respectively). On theother hand, the ratios of unpopular videos were significantly higher than thoseof popular videos concerning introduction of materials (20.2% and 0.0%,
respectively), introduction of events or programs, both reporting (26.6% and7.5%, respectively) and notification (25.7% and 12.1%, respectively),
introductions of displays (12.8% and 0.0%, respectively), and unknowns (5.5%
and 0.0%, respectively).
Table 13. Video Contents

Popular Unpopular
Providing(n=107)(n=109)0.0%

20.2% **

Tutorials

28.0% **

6.4%

Other information services

0.0%

0.9%

Story times

21.5% *

10.1%
6.4%

Information services Introduction of materials

library services
Targeted services
Introduction ofGeneral introductions or promotion videos

9.3%

the library

Introduction of services

26.2% **

6.4%

Introduction of events or programs (report)

7.5%

26.6% **

Introduction of events or programs (notification)

12.1%

25.7% *

Introduction of their particular buildings, spaces, or facilities

1.9%

4.6%

Introduction of their displays

0.0%

12.8% **

Introduction of other things

3.7%

3.7%

Entertainments, comedies, or videos to build a familiarity

14.0% **

0.0%

Asking for supports

0.9%

3.7%

Reading promotion videos

0.9%

0.0%

Others2.8%

1.8%

Unknowns

0.0%

5.5% *

4.7 Results concerning the Cast Members
Table 14 displays the numbers of cast members in the videos. In Table 14,‘2~3’ represents the videos in which cast members were two or three people,
and ‘4~’ represents the videos which included four or more cast members.
There was no significant difference between popular and unpopular videos
concerning the number of cast members. It was found that there was at least
one cast member in 73 popular and 73 unpopular videos.
In addition, we investigated the racial makeup among cast members using
Betaface when there were three or fewer cast members. Table 15 shows thegeneral racial distribution among cast members of popular and unpopular
videos. ‘Unknown’ refers to the videos that were judged as showing no faces.
Table 15 shows that there were no African American6 cast members in the
popular videos, and there was only one African American cast member in one
unpopular video. In addition, we randomly selected ten unpopular and popular
videos (a total of 20 videos) with a number of cast members at four or more andinvestigated the role of each cast member. Concerning popular videos,librarians appeared in eight videos. In these videos, one librarian appeared in
one video, two librarians appeared in one video, seven librarians appeared in
one video, nine librarians appeared in one video, and ten or more librarians
appeared in four videos. In the unpopular videos, librarians appeared in eight
videos. In these videos, one librarian appeared in six videos, two librarians
appeared in one video, and three librarians appeared in three videos.
Table 14. Number of Cast Members
Popular

Unpopular(n=107)(n=109)

0

34

36

1

24

35

2〜3

12

12

4〜

37

26

Table 15. Race of Cast Members
n

White

Asian

IndianAfrican American Mideast

Unknown

Popular

49

37

6

3

0

0

2

Unpopular

66

49

3

0

1

1

9

5. Discussions
The first factor of libraries’ success with YouTube that we will discuss regards
the length of the videos. The analysis found that unpopular videos were often
extremely short (less than 10 seconds) or very long (over 20 minutes). It isquite possible that people quit watching the videos if the videos were too longor too short. In addition, popular videos tended to have longer titles and include
descriptions more often, compared with unpopular ones. Our analysis has
determined that the popular videos were more informative than the unpopular
ones. The results regarding video contents indicated that popular videos tended
to provide information about library services. These videos tended to offer
tutorials or story times. On the other hand, the ratios of event reports and event
notices among popular videos were significantly lower than those among
unpopular ones.
It is interesting to note that popular videos included three Spanish videos
and one sign language video. This finding may indicate that YouTube videos
could be effective ways to provide services for underserved communities, suchas speakers of English as a second language or sign language speakers.
Moreover, as we describe above, many libraries provide library services such as
information services and children’s services via YouTube. This means that
YouTube videos can be helpful not only for speakers of foreign language but
also for people with disabilities who might not be able come into libraries
regularly.
Next, the second key factor in libraries’ uses of YouTube concerns castmembers of the videos in our sample, beginning with race. For videos withthree or fewer cast members, none of the popular videos and one of theunpopular videos included African American cast members. This was only
0.9% of our sample cast members. The 2010 census of U.S. showed that theratio of black or African American people living in the U.S. was 12.3%. The
ratio of African American people appearing in libraries’ YouTube videos was
significantly lower than the number of African American people living in the
U.S. according to the census report.
Another factor for success with YouTube video views concerns librarians.
In relation to the videos with four or more cast members, many librarians
appeared in popular videos whereas few librarians appeared in unpopular
videos. In the videos where many librarians appeared, librarians often
explained how wonderful the libraries were. In order to provide such
explanations, librarians might strive to create varied and detailed elements ofvideos, and thus they might produce more popular and higher-quality videos. In
addition, it is easy for video viewers to recommend such videos to their friends,
including students or new residents, and these high view counts for this style ofvideo may occur as a result.

6. Conclusions
In this paper, we focused on YouTube videos made by U.S. public libraries,
showing the actual state of libraries’ YouTube utilization and the factors that
increase their views. Specifically, we first examined how many public libraries
were utilizing each social media platform, including YouTube, based oninformation from their official websites. In addition, we compared 107 popular
videos (having more than 700 views) and 109 unpopular ones (having fewer
than 12 views) and analysed their differences. Results showed that theunpopular videos were often very short (less than 10 seconds) or very long(over 20 minutes). The popular videos were more informative than theunpopular ones (e.g. they had longer titles which explained the contents of thevideos). Furthermore, the ratios of tutorials and story time among popular
videos were significantly higher than those among unpopular ones.
Nevertheless, the ratios of event reports and event notices among popular
videos were significantly lower than those among unpopular ones. Further, theresults suggested the potential effectiveness of YouTube to provide services forminority and underserved populations. In fact, the ratio of African American
people appearing in libraries’ YouTube videos was significantly lower than thatof the U.S. population, according to the last census report.
In future study of this area, we would like to increase the sample size. In
addition, we would like to investigate these factors in relation to other social
media. Such additional work is needed to identify more effective methods forboth providing information and in marketing of libraries.

Acknowledgment
This work was supported by JSPS KAKENHI Grant Number JP19K20632.

Notes
1

http://www.americanlibrarydirectory.com/AdvSearch.asp
The number of libraries’ accounts and the number of unique accounts were
not equal because some libraries shared one account. For example, two of
our sample libraries shared the ‘Four County Library System’ account.
3
Before starting this investigation, the official websites had been updated, andthe link to YouTube video content had apparently been deleted.
4
We excluded the accounts that posted many times because it could influence t
factors other than the factors of the video itself.
5
We excluded the videos because fewer view counts were caused not by thevideo itself but by the brief time that the video had been online.
6‘African Americans’ used here were people referred to as ‘Black’ inBataface.
2

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