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Utilizing HTML ‐analysis and computer vision on a corpus of website screenshots to investigate design developments on the web

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Utilizing HTML ‐analysis and computer vision on a corpus of website screenshots to investigate design developments on the web

Abstract

We present preliminary results of a project investigating the design development of popular websites between 1996 and 2020 via HTML analysis and basic computer vision methods. We acquired a corpus of website screenshots of the current top 47 popular websites. We crawled a snapshot of every month of these websites via the wayback machine of the Internet Archive platform since the time snapshots are stored to gather 7,953 screenshots and HTML pages. We report upon quantitative analysis results concerning HTML elements, color distributions and visual complexity throughout the years.
POSTERS
Utilizing HTML-analysis and computer vision on a corpus
of website screenshots to investigate design developments
on the web
Thomas Schmidt | Anastasiia Mosiienko | Raffaela Faber | Juliane Herzog |
Christian Wolff
Media Informatics Group, University of
Regensburg, Regensburg, Germany
Correspondence
Thomas Schmidt, Media Informatics
Group, University of Regensburg,
Regensburg, Germany.
Email: thomas.schmidt@ur.de
Abstract
We present preliminary results of a project investigating the design develop-
ment of popular websites between 1996 and 2020 via HTML analysis and basic
computer vision methods. We acquired a corpus of website screenshots of the
current top 47 popular websites. We crawled a snapshot of every month of
these websites via the wayback machine of the Internet Archive platform since
the time snapshots are stored to gather 7,953 screenshots and HTML pages.
We report upon quantitative analysis results concerning HTML elements, color
distributions and visual complexity throughout the years.
KEYWORDS
colors, html, visual complexity, web design, web history, websites
1|INTRODUCTION
The World Wide Web has become an important part
of modern media infrastructure and society. The web
itself has also become an object of research in
human-computer-interaction (Jørgensen & Myers,
2008) but also cultural and media studies
(Brügger, 2012). Investigating the history of web
interfaces is an important task for web and media his-
torians but can also give current web designers inspi-
ration on how developments might continue. One
important aspect of this research area is the archival
of the web and the preservation of this digital heri-
tage has been addressed by the UNESCO.
1
This led to
the platform Internet Archive,
2
which, via its
Wayback Machine
3
intends to archive the web and
enables design researchers to investigate trends on
large-scale corpora. We present work-in-progress
results of a project investigating web design
developments via quantitative and qualitative analy-
sis. We report on our current approach and the first
quantitative results we acquired.
2|METHODS
2.1 |Corpus-acquisition
We decided to analyze the top 50 most popular websites
as of December 2019 according to the analytical platform
Alexa.
4
We filtered out any adult websites, which resulted
in a list of 47 websites. We acquired one snapshot per day
of these websites stored in the Wayback Machine, if a
snapshot was available for the timespan from 1996 to
2020. A snapshot is a stored representation of the website
for a given time. This results in a corpus of 151,682 snap-
shots. However, all websites are represented rather
unequally with the most popular and oldest being most
DOI: 10.1002/pra2.392
83rd Annual Meeting of the Association for Information Science & Technology October 25-29, 2020.
Author(s) retain copyright, but ASIS&T receives an exclusive publication license
Proc Assoc Inf Sci Technol. 2020;57:e392. wileyonlinelibrary.com/journal/pra2 1of5
https://doi.org/10.1002/pra2.392
frequent. For this study, we limited this corpus to one
snapshot per month per website (the first available snap-
shot per month) to avoid problems with the unequal dis-
tribution. This subcorpus consists of 7,953 snapshots
(Tables 1 and 2) of which we scraped the HTML and took
a screenshot as TIFF-File with a width of 1920 pixels and
height according to the size of website. To enable com-
parisons, we sliced the screenshots at 3000 pixels height.
The sample size for the early years is rather limited.
However, beginning 2003 the sample size is more
representative with around 300 snapshots per year. Fig-
ures 1 and 2 show two snapshots of amazon.com.
2.2 |Analysis metrics
We analyzed multiple quantitative metrics: (a) HTML
metrics, (b) screenshot size, and (c) color metrics. We
counted the number of images via the img-tag, the num-
ber of hyperlinks via the a-tag and the overall amount of
words in the HTML. Another metric is the size of the
screenshots measured in kilobytes after transforming
TABLE 1 Websites of the corpus and number of snapshots
Website #snapshots Website #snapshots Website #snapshots Website #snapshot
360.cn 152 Facebook.com 200 Office.com 98 Twitter.com 183
Aliexpress.
com
121 Google.co.in 194 Okezone.com 155 Vk.com 169
Alipay.com 121 Google.com.hk 199 qq.com 202 Weibo.com 103
Amazon.co.jp 161 Google.com 242 Reddit.com 179 Wikipedia.org 191
Amazon.com 203 Instagram.com 114 Sina.com 218 Wordpress.
com
184
Apple.com 242 Jd.com 132 Sohu.com 227 Xinhuanet.
com
228
Babytree.com 184 Live.com 102 Stackoverflow.
com
138 Yahoo.co.jp 245
Baidu.com 216 Login.tmall.com 92 Taobao.com 126 Yahoo.com 255
Bing.com 159 Microsoftonline.
com
124 Tianya.cn 169 Yandex.ru 220
Blogspot.com 107 msn.com 241 Tmall.com 128 Youtube.com 178
Csdn.net 214 Naver.com 229 Tribunnews.com 110
Ebay.com 240 Netflix.com 153 Twitch.tv 105
TABLE 2 Website distribution per year
Year #snapshots Year #snapshots
1996 10 2009 378
1997 23 2010 412
1998 26 2011 487
1999 70 2012 494
2000 150 2013 500
2001 183 2014 487
2002 182 2015 491
2003 284 2016 484
2004 317 2017 503
2005 349 2018 498
2006 362 2019 501
2007 394 2020 30
2008 338
FIGURE 1 Snapshot of Amazon.com (1998)
2of5 SCHMIDT ET AL.
them to PNG-files. This is an established metric to mea-
sure visual complexity and has been shown to correlate
withhumanperceptionofcomplexity(Purchase
et al., 2012); the larger the more complex an image. We
calculated the amount of the base colors red, green,
blue,yellowaswellaswhiteandblackviaopenCV.
5
Table 3 gives an overview of the RGB-sections we
included.
3|RESULTS
We averaged the number of image-tags, hyperlink-tags
and the text per year (see Figures 35).
For the number of images and hyperlinks we can
identify a steady increase up until 2014 followed by a sub-
stantial decrease. A similar development can be found for
text up until 2016.
Figure 6 shows the development of the average visual
complexity as measured via the filesize.
For this metric, we identified a steady increase until
2020, with the highest leap in the time span from 2009
until 2014.
The color analysis shows that black and white are the
most dominant colors since white is the general back-
ground color and black the basic font color. Figure 7
illustrates the average proportion of black and white
among the websites and shows that most websites consist
to around 80% percent of white. However, we observe a
small decrease up until now.
While the overall proportion is much lower, we identi-
fied red and blue as the most used among the base colors,
however without a consistent trend (Figure 8). Beginning
with 2013, we can see a more diverse distribution among
our analyzed colors. Nevertheless, without a striking
trend or development. Please note that the proportions
are overall very low, so the significant usage of very popu-
lar websites of one color for a year can lead to strong
manifestations of this color which is especially the case
for years we do not have many snapshots for (19962003).
4|DISCUSSION
We identified a steady increase of HTML-tags up until
2014 and a remarkable decrease afterwards. A similar but
less strong trend is found for the number of words. We
hypothesize that these results represent a trend in web
design to include more content up until 2014, which is
FIGURE 2 Snapshot of Amazon.com (2020)
TABLE 3 Overview of the used RGB color ranges
Color Lower limit (R,G,B) Upper limit (R,G,B)
Red (140, 0, 0) (255, 56, 50)
Green (0, 170, 0) (130, 255, 70)
Blue (0, 0, 145) (60, 115, 255)
Yellow (230, 220, 0) (255, 255, 55)
White (240, 240, 240) (255, 255, 255)
Black (0, 0, 0) (25, 25, 25)
FIGURE 3 Average number of images per year
FIGURE 4 Average number of hyperlinks per year
FIGURE 5 Average number of words per year
SCHMIDT ET AL.3of5
certainly connected to increased technical possibilities.
Snapshots of msn.com in our corpus are representative of
this trend (Figures 9 and 10).
After 2014, this trend is followed by a tendency toward
more minimalistic designs. This is opposite to the steady
increase of visual complexity. The reason for the develop-
ment of this metric, however, might also be the possibility
for designers to include more complex images and graphs
with the advent of bandwidth. While the usage of black
and white is dominant on websites until now, we identi-
fied a higher usage of red and blue in early days and a more
diverse color usage beginning 2013. Our color analysis is
however very limited since we neglect a wide range of
other colors.
We want to continue our research by including other
quantitative metrics like alternatives for visual complexity
and other colors and by analyzing the websites by cate-
gory. We plan to increase the corpus, especially with
websites that were popular in the years 19962010 and are
not nowadays to get a more representative sample of these
times. We pursue a mixed methods approach and want to
integrate qualitative analysis of a subset of the corpus to
get a better understanding of design developments.
ENDNOTES
1
https://en.unesco.org/themes/information-preservation/digital-
heritage
2
https://archive.org/
3
https://archive.org/web/
4
https://www.alexa.com/
5
https://opencv.org/
FIGURE 6 Average size of PNG-files per year
FIGURE 7 The average proportion of black and white among
websites
FIGURE 8 The average proportion of red, blue, green and
yellow per year
FIGURE 9 Snapshot of Msn.com (1996)
FIGURE 10 Snapshot of Msn.com (2014)
4of5 SCHMIDT ET AL.
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Brügger, N. (2012). When the present web is later the past: Web his-
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Purchase, H. C., Freeman, E., & Hamer, J. (2012). An exploration of
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How to cite this article: Schmidt T, Mosiienko A,
Faber R, Herzog J, Wolff C. Utilizing HTML-
analysis and computer vision on a corpus of
website screenshots to investigate design
developments on the web. Proc Assoc Inf Sci
Technol. 2020;57:e392. https://doi.org/10.1002/
pra2.392
SCHMIDT ET AL.5of5
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