Tag cloud | EPFL Graph Search

Are you an EPFL student looking for a semester project?

Work with us on data science and visualisation projects, and deploy your project as an app on top of GraphSearch.

A tag cloud (also known as a word cloud, wordle or weighted list in visual design) is a visual representation of text data which is often used to depict keyword metadata on websites, or to visualize free form text. Tags are usually single words, and the importance of each tag is shown with font size or color. When used as website navigation aids, the terms are hyperlinked to items associated with the tag. In the language of visual design, a tag cloud (or word cloud) is one kind of "weighted list", as commonly used on geographic maps to represent the relative size of cities in terms of relative typeface size. An early printed example of a weighted list of English keywords was the "subconscious files" in Douglas Coupland's Microserfs (1995). A German appearance occurred in 1992. The specific visual form and common use of the term "tag cloud" rose to prominence in the first decade of the 21st century as a widespread feature of early Web 2.0 websites and blogs, used primarily to visualize the frequency distribution of keyword metadata that describe website content, and as a navigation aid. The first tag clouds on a high-profile website were on the photo sharing site Flickr, created by Flickr co-founder and interaction designer Stewart Butterfield in 2004. That implementation was based on Jim Flanagan's Search Referral Zeitgeist, a visualization of Web site referrers. Tag clouds were also popularized around the same time by Del.icio.us and Technorati, among others. Oversaturation of the tag cloud method and ambivalence about its utility as a web-navigation tool led to a decline of usage among these early adopters. Flickr gave a five-word acceptance speech for the 2006 "Best Practices" Webby Award, which simply stated "sorry about the tag clouds." A second generation of software development discovered a wider diversity of uses for tag clouds as a basic visualization method for text data. Several extensions of tag clouds have been proposed in this context. There are three main types of tag cloud applications in social software, distinguished by their meaning rather than appearance.

About this result

This page is automatically generated and may contain information that is not correct, complete, up-to-date, or relevant to your search query. The same applies to every other page on this website. Please make sure to verify the information with EPFL's official sources.

Related publications (26)

Related people (4)

Related units (4)

Related concepts (5)

Related lectures (6)

Folksonomy

Folksonomy is a classification system in which end users apply public tags to online items, typically to make those items easier for themselves or others to find later. Over time, this can give rise to a classification system based on those tags and how often they are applied or searched for, in contrast to a taxonomic classification designed by the owners of the content and specified when it is published. This practice is also known as collaborative tagging, social classification, social indexing, and social tagging.

Enterprise bookmarking

Enterprise bookmarking is a method for Web 2.0 users to tag, organize, store, and search bookmarks of both web pages on the Internet and data resources stored in a distributed database or . This is done collectively and collaboratively in a process by which users add tag (metadata) and knowledge tags. In early versions of the software, these tags are applied as non-hierarchical keywords, or terms assigned by a user to a web page, and are collected in tag clouds. Examples of this software are Connectbeam and Dogear.

Tag (metadata)

In information systems, a tag is a keyword or term assigned to a piece of information (such as an Internet bookmark, multimedia, database record, or ). This kind of metadata helps describe an item and allows it to be found again by browsing or searching. Tags are generally chosen informally and personally by the item's creator or by its viewer, depending on the system, although they may also be chosen from a controlled vocabulary. Tagging was popularized by websites associated with Web 2.

The rapidly increasing amount of user-generated content in social tagging systems provides a huge source of information. Yet, performing effective search in these systems is very challenging, especially when we seek the most appropriate items that match a ...

Assoc Computing Machinery2014

Unison Cache: A Scalable and Effective Die-Stacked DRAM Cache

Babak Falsafi, Ilknur Cansu Kaynak

Recent research advocates large die-stacked DRAM caches in manycore servers to break the memory latency and bandwidth wall. To realize their full potential, die-stacked DRAM caches necessitate low lookup latencies, high hit rates and the efficient use of o ...

IEEE2014

Multi-factor Segmentation for Topic Visualization and Recommendation: the MUST-VIS System

Andrei Popescu-Belis, Sandy Ingram, Nikolaos Pappas, Maryam Habibi

This paper presents the MUST-VIS system for the MediaMixer/VideoLectures.NET Temporal Segmentation and Annotation Grand Challenge. The system allows users to visualize a lecture as a series of segments represented by keyword clouds, with relations to other ...

ACM2013

Memory Consistency Models CS-307: Introduction to multiprocessor architecture

Explores memory consistency models, cache coherence, and processor performance factors.

Heat Pump Tutorial ME-454: Modelling and optimization of energy systems

Explains the steps to define a heat pump and thermal streams.

Social Image Systems: Past, Present, and Research Insights DH-500: Computational Social Media

Explores social image systems, from past practices to present platforms and research insights, including tagging motivations and participatory culture.