![](bg3.png)
A few studies verifying effectiveness of tag clouds
and user experience have been conducted. List of
tasks that tag clouds can support: Search, Browsing,
Impression Formation and Recognition/Matching is
given by (Rivadeneira et al., 2007). Out of these, the
last one means verifying whether tag cloud is rep-
resenting particular subject. Note that only Search
is goal-oriented task, while the remaining are rather
free browsing tasks. (Halvey and Keane, 2007) per-
formed simple experiment with time necessary for
finding certain tag, and they found that alphabetical
list is actually faster. They also conclude that users
rather scan than read tag clouds. When testing clouds
obtained from their algorithm, (Seifert et al., 2008)
used a different approach. Namely, they asked users
to point three most important tags and measured the
correctness. Though this seems a better idea for eval-
uating tag clouds, their experiments were strongly re-
lated to their algorithms and give no general insights.
(Rivadeneira et al., 2007) on the basis of their re-
sults, conclude that font size and location affect low-
level memory processes, while layout high-level ones,
such as impression formation. They suggest to fo-
cus on the layout of tag cloud. Research of (Bate-
man et al., 2008) did not tackle the layout matters,
instead font related parameters were tested leading
to conclusions that larger and stronger fonts draw
more users attention, while color although being well
recognized proves difficulties in visualizing impor-
tance. (Lohmann et al., 2009) performed several ex-
periments on performance of certain tasks involving
various cloud layouts. They confirm earlier findings
of (Halvey and Keane, 2007) that finding a specific
tag is fastest with alphabetical sorting and that users
are scanning rather than reading. Yet, their other ex-
periments show that for finding most important tags,
recalling tags, etc. layout plays important role.
The above presented research was focused on
goal-orientated tasks, which are easier to measure, as
opposed to free browsing tasks. However, browsing
is an important application of tag clouds.
2.2 For the Web
In authors’ opinion, tag clouds for websites have to
meet additional requirements. Website space is al-
ways rectangular and scarce so it should be used
wisely. This gives a preference to tag clouds fill-
ing a rectangular envelope well. As websites usually
use column layout (Marszałkowski and Drozdowski,
2013) horizontal size of a tag cloud is fixed, while the
vertical size can be changed, thus moving the com-
ponent below up or down a little. This characteristic
resembles strip packing problems.
A tag cloud for a website should use standard
technologies, making a reasonable trade-off between
fancy looks and the simplicity of the code. This has
two reasons: Firstly, it is a matter of the ease of imple-
mentation. Secondly, not only humans read websites
and making website content available to the robots
is of great importance (see (Marszalkowski et al.,
2014)). Using HTML with JavaScript (JS) and CSS as
simple as possible seems to be a natural decision here.
This simplifies some of the further choices: Though
the use of exact tag shapes or tag rotation are possi-
ble in most modern browsers, they are not standard
and cannot be guaranteed to work perfectly the same
way for every client. Hence, they should be discour-
aged. The same argument can be applied in prefer-
ing the alignment to the baselines over the freedom
of arbitrary 2D packing. Tags on a baseline will be
considered just as line of text by the robots. Taking
into account the results of the studies demonstrating
that users scan lines of the clouds (see Section 2.1),
the use of baselines will make reading tags more effi-
cient.
Next we come to the choice of tag ordering. It was
already mentioned that alphabetical clouds perform
worse in the speed of searching compared to lists, so
why to use them? Moreover, alphabetical ordering
significantly restricts flexibility of packing in two fol-
lowing ways. Firstly, since tags cannot be reordered
the only remaining option is to choose where to put a
line break. Secondly, for the same reason use of dif-
fering font sizes must remain limited, as tags of the
smallest font cannot be moved away from the lines
made very tall by the tags of the greatest font size.
To achieve any reasonable visual quality tags have to
be rearranged, i.e. the sequence tags should follow
packing.
Our design recommendations are: 1) tags are re-
ordered with packing, 2) minimum waste of the rect-
angular area is desired, 3) tags are rectangular boxes,
4) rotation is not allowed, 5) tags fit between base-
lines (shelves). Although it may seem that in most
cases simplifying choices were made, we end up with
a problem that can be expected to rest in NP-hard
class. Thus, it can be expected that optimum solu-
tions (e.g. in the sense of used area) can be deliv-
ered by exponential-time algorithms. The current rec-
ommendation encompasses bin packing problems or
strip packing which can be solved by use of shelf al-
gorithms, or metaheurisitcs (Burke et al., 2006).
2.3 Client Side
In times of more and more personalized content each
user can get a different set of tags. But there is more