A tag cloud ( word cloud , or weighted list in visual design) is a new visual representation of text data, typically used to describe keyword metadata (tags) on a website, or to visualize free-form text. Tags are usually single words, and the importance of each tag is indicated by font size or color. This format is useful for quickly understanding the most prominent terms and for finding the term alphabetically to determine its relative superiority. When used as a website navigation tool, the term is hyperlinked to an item associated with the tag.
Video Tag cloud
History
In the visual design language, the tag cloud (or word cloud) is one of the "weighted list" types, as is commonly used on geographic maps to represent relative size of the city in terms of relative typographic size. Early print examples of a weighted list of English keywords are "subliminal files" in Douglas Coupland Microserfs (1995). German appearance occurred in 1992.
The specific visual form and the general use of the term "tag cloud" rose to prominence in the first decade of the 21st century as a widespread feature of the early 2.0 websites and blogs, primarily used to visualize the frequency distribution of keyword metadata that describe the website. content, and as a navigation aid.
The first cloud tag on high profile websites is on the Flickr photo sharing website, created by Flickr founder and interaction designer Stewart Butterfield in 2004. The implementation is based on Jim Flanagan's Zeitgeist Search Referrals, website referrer visualizations. The tag cloud was also popularized around the same time by Del.icio.us and Technorati, among others.
Oversaturation of the cloud tag method and ambivalence about its utility as a web navigation tool causes the decline in usage recorded among these early users. (Flickr would then "apologize" to the web development community in their five-word acceptance speech for the 2006 "Best Practices" Webby Award, where they simply stated "sorry about tag cloud.")
The second generation of software development found a wider use of diversity for tag clouds as a basic visualization method for text data. Several extensions of tag cloud have been proposed in this context. Examples include Parallel Clouds Tags, SparkClouds, and Tag Clouds Prefix. The Word Cloud Explorer, written in Adobe Flex, combines tag clouds with a number of interactive features for text analysis.
Maps Tag cloud
Type
There are three main types of cloud tag apps in social software, differentiated by meaning rather than appearance. In the first type, there is a tag for the frequency of each item, whereas in the second type, there is a global tag cloud where frequency is collected across all items and users. In the third type, the cloud contains categories, with sizes indicating the number of subcategories.
Frequency
In the first type, the size indicates how many times the tag is applied to an item. This is useful as a means of displaying metadata about items that are democratically "selected" and where precise results are not desired. Examples of such uses include Last.fm (to show the genres associated with the band) and LibraryThing (to show tags associated with the book).
In the second section, the more commonly used type, the size representing the number of items that tags have applied, as a presentation of each tag's popularity. Examples of these cloud tag types are used on the Flickr image hosting service, Technorati aggregator blog and Google search results with DeeperWeb.
Significance
Instead of frequency, the size can be used to represent word signficance and co-incident words, as compared to the background corpus (eg, compared to all the texts on Wikipedia). This approach can not be used alone, but it depends on the document frequency comparison with the expected distribution.
Categorization
In the third type, tags are used as categorization methods for content items. The tags are represented in a cloud where larger tags represent the quantity of content in that category.
There are several approaches to creating tag clusters instead of cloud tags, for example, by applying co-occurrences tags in a document.
More generally, the same visual technique can be used to display non-tag data, as in the word cloud or cloud data.
The term keyword cloud is sometimes used as a search engine marketing term (SEM) that refers to a group of keywords relevant to a particular website. In recent years, cloud tags have gained popularity for their role in search engine optimization of web pages and support users in navigating content in an information system efficiently. The cloud tag as a navigation tool makes website resources more connected, when crawled by search engine spiders, which can improve the site's search engine ranking. From the perspective of their user interface is often used to summarize the search results to support users in finding content in certain information systems more quickly.
Visual views
Cloud tags are usually represented using inline HTML elements. Tags can appear in alphabetical order, in random order, they can be sorted by weight, and so on. Sometimes, the visual property is further manipulated in addition to font size, such as font color, intensity, or weight. Most popular is the arrangement of rectangular tags by sorting alphabetically in sequential line-by-line order. Decisions for optimum layout should be driven by the intended purpose of the user. Some prefer to group tags semantically so similar tags will appear near each other or use embed techniques like tSNE to position the word. Edges can be added to emphasize co-occurrence tags and visualize interactions. Heuristics can be used to reduce the size of the tag cloud whether the goal is to group tags.
The cloud visual taxonomy tag is determined by a number of attributes: tag ordering rules (eg alphabetically, by importance, contextually, randomly, ordered for visual quality), overall cloud form (eg rectangles, circles, given map boundaries) tag (rectangle, or body of characters), tag rotation (none, free, limited), vertical tag alignment (sticking to baseline typography, free). A tag cloud on the web should address modeling issues and control aesthetics, build a two-dimensional layout of tags, and all of this should be done in a short period of time on a volatile browser platform. The cloud tags that will be used on the web must be in HTML, not graphics, to make them readable by robots; they must be built on the client side using the fonts available in the browser, and they must be in rectangular boxes.
Cloud data
A cloud data or cloud data is a data view that uses font and/or color sizes to indicate numerical values. This is similar to the cloud tag but not the number of words, displaying data such as population or stock market prices.
Cloud text
A text cloud or the cloud word is the visualization of the word frequency in a given text as a weighted list. This technique has recently been popularly used to visualize the content of political speech.
Cloud location
Expanding the principles of cloud text, cloud collocate provides a more focused view of documents or corpus. Instead of summarizing the entire document, the collocate cloud checks the use of certain words. The resulting cloud contains frequently used words along with the search term. This collocation is formatted to show the frequency (as a measure) as well as the strength of collocation (as brightness). It provides an interactive way to explore and explore languages.
Perception
Tag cloud has been the subject of investigation in several usability studies. The following summary is based on an overview of research results provided by Lohmann et al.
- Tag size: Large tags attract more user attention than small tags (effects are affected by more properties, e.g., Ã, number of characters, position, neighbor tags).
- Scan: Users scan rather than read tag clouds.
- Centering: The tags in the center of the cloud attract more user attention than tags near the border (effects affected by the layout).
- Position: The upper left quadrant receives more user attention than others (Western reading habits).
- Exploration: The cloud tag provides suboptimal support when searching for specific tags (if this does not have a very large font size).
Felix et al. comparing how the performance of human reading differs from traditional tag clouds that map numeric values ​​to font sizes and alternative designs that use for example additional colors or shapes like circles and blades. They also compare how different word settings affect performance.
- Use an additional bar or circle instead of letter size to improve accuracy when reading numeric values ​​
- However users can find certain words faster when no additional tags are used
- Performance is dependent on tasks, simple tasks such as finding words are strongly influenced by design choices, but effects on tasks such as identifying the topic from tag cloud are much smaller.
Creation
Since the number of items indexed per descriptor is usually distributed according to the law of force, for a larger range of values, logarithmic representations make sense.
Tag cloud implementation also includes parsing text and filtering out unhelpful tags like common words, numbers, and punctuation.
There are also web sites that create artificial or randomly generated tag clouds, for ads, or for funny results.
See also
- Conformity
- Folksonomy
- Keywords
- tf-idf
References
External links
- Understand Tag Clouds - design information analysis from tag cloud
- Design tips for building tag clouds - software development guide from O'Reilly's ONLamp
- 9 Word Cloud generators in one place - all free to experiment.
Source of the article : Wikipedia
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