Introduction to Tags and Tag Clouds

A tag is a keyword or term associated with a piece of content. In the context of Bentley Communities, that is a forum post, wiki or blog article, file or image, idea, etc. It links the content to other content that it relates to contextually. Tags give you flexibility in structuring a Web site and in helping map information. Tags also make the information on a Web site more discoverable and accessible via search engines.

You can take advantage of searching for information that has tags associated to it by using something like a tag cloud. Tag clouds scope to the content they represent. For example, a tag cloud that might exist on community home page focusing on animals might look like this:

Tags listed in a tag cloud are used in all community applications (e.g. forums, blogs, wikis, etc.) in varying numbers. The tags are listed alphabetically and their relative point sizes can change to represent how frequently the tags used. In this example, "cat" and "kangaroo" are the largest because they're used most frequently (note that we do not currently do that in Bentley Communities).

How does this help with searching for information? Quite simply, a tag cloud contains a list of tags that link to search results of content which include that tag. You could click "elephant," for instance, and see the posts that contain this tag. If the widget is placed on a Web site’s home page, the result of clicking “elephant” would be all posts in all communities and applications across that site with that tag. If the widget is placed on a blog home page, the results would be only the blog articles with that tag in that community blog. This is why the tag cloud more often than not looks different from one page to another on a Web site where it is used.

Of course, searching for information via tag cloud yields more positive results when content is tagged in a consistent and judicious manner. When posting anything on Be Communities, for example, including a few tags that identify the main context of what you are posting (e.g. product name, functional area, product version, language, etc.) will make it that much easier for anyone to find. So before clicking “Post”, remember to include tags so you (and our users) can take advantage of the benefits that tag clouds provide.

Our process to create Support Solutions wiki articles has been designed and implemented to help with tagging, both from a consistency and a process perspective. Some tags (e.g. product name, product keyword, etc.) are consistent and associated with these articles when they are created. Other tags will be “freeform”, but should come from one or more various sources (e.g. SEO keyword lists of search terms across Bentley Web properties, identifying the primary context of an article, etc.)

At a minimum, any piece of content (e.g. forum thread, Support Solution wiki article, etc.) should have the following tags: 

What Required  
Product Name Mandatory
Product Area Mandatory
Product Sub-area Optional
Product Version # Optional
Bentley Topic Optional
Content Topic 1 Optional
Content Topic 2 Optional
Content Topic 3 Optional
Content Topic 4 Optional
SEO Search Word 1 Optional
SEO Search Word 2 Optional
SEO Search Word 3 Optional

Something worth considering in using to identify or select “freeform” content topic tags is a web site called, which can analyze text or a web page or a file and provide suggestions as to what tags to use. For example: 

  1. Go to
  2. Paste some text or enter a URL of a page (i.e.
  3. Press <Enter>

The result shows the top 50 (or whatever you set the maximum number of words to show to) non-modifier words used multiple times from the text/URL/file processed. Like this for the above URL:

The words with the largest point size could be used as the “freeform” tags in addition to the mandatory ones to be added or edited to your content. The reason for doing this is to make the content more “discoverable” when anyone searches for something. The tag suggestions help minimize the guesswork of trying to figure out what to use as tags by identifying the main points the article relates to.

When an article is localized, the tags should be localized, too. This helps with the searchability of content in other languages.

Although not specifically covered in this article, the same applies to #hashtags, too.