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| title | chunk | source | category | tags | date_saved | instance |
|---|---|---|---|---|---|---|
| Discoverability | 4/4 | https://en.wikipedia.org/wiki/Discoverability | reference | science, encyclopedia | 2026-05-05T07:22:29.265231+00:00 | kb-cron |
=== Algorithms === In the digital economy, sophisticated algorithms are required for the analysis of the ways that end users search for, access and use different content or products online. Thus, not only is metadata created regarding the content or product, but also data about specific users' interaction with this content. If a social media website has a user profile for a given person, indicating demographic information (age, gender, location of residence, employment status, education, etc.), then this website can collect and analyse information about tendencies and preferences of a given user or a subcategory of users. This raises potential privacy concerns. Algorithms have been called “black boxes”, because the factors used by the leading websites in their algorithms are typically proprietary information which is not released to the public. While a number of search engine optimization (SEO) firms offer the services of attempting to increase the ranking of a client's web content or website, these SEO firms do not typically know the exact algorithms used by Google and Facebook. Web crawlers can only access 26% of new online content "...by recrawling a constant fraction of the entire web". One concern raised with the increasing role of algorithms in search engines and databases is the creation of filter bubbles. To give a practical example, if a person searches for comedy movies online, a search engine algorithm may start mainly recommending comedies to this user, and not showing him or her the range of other films (e.g., drama, documentary, etc.). On the positive side, if this person only likes comedy films, then this restricted "filter" will reduce the information load of scanning through vast numbers of films. However, various cultural stakeholders have raised concerns about how these filter algorithms may restrict the diversity of material that is discoverable to users. Concerns about the dangers of "filter bubbles" have been raised in regards to online news services, which provide types of news, news sources, or topics to a user based on his/her previous online activities. Thus a person who has previously searched for Fox TV content will mainly be shown more Fox TV content and a person who has previously searched for PBS content will be shown more PBS search results, and so on. This could lead to news readers becoming only aware of a certain news source's viewpoints. The search behaviour of video content viewers has changed a great deal with increasing popularity of video sharing websites and video streaming. Whereas a typical TV show consumer of the 1980s would read a print edition of TV Guide to find out what shows were on, or click from channel to channel ("channel surfing") to see if any shows appealed to them, in the 2010s, video content consumers are increasingly watching on screens (either smart TVs, tablet computer screens or smartphones), that have a computerized search function and often automated algorithm-created suggestions for the viewer. With this search function, a user can enter the name of a TV show, producer, actor, screenwriter or genre to help them find content of interest to them. If the user is using a search engine on a smart device, this device may transmit information about the user's preferences and previous online searches to the website. Furthermore, in the 1980s, the type or brand of television a user was watching on did not affect his/her viewing habits. However, a person searching for TV shows in the 2010s on different brands of computerized smart TVs will probably get different search results for the same search term.
=== Limitations === For organizations that are trying to get maximal user uptake of their product, discoverability has become an important goal. However, achieving discovery does not automatically translate into market success. For example, if the hypothetical online game "xyz" is easily discoverable, but it will not function on most mobile devices, then this video game will not perform well in the mobile game market, despite it being at the top of search results. As well, even if the product functions, that is it runs or plays properly, as well, users may not like the product. In the case that a user does like a certain online product or service, the discoverability has to be repeatable. If the user cannot find the product or service on a subsequent search, she or he may no longer look for this product/service, and instead shift to a substitute that is easily and reliably findable. It is not enough to make the online product or service discoverable for only a short period, unless the goal is only to create “viral content" as part of a short-term marketing campaign.
== See also == Findability Information foraging Service-oriented architecture WSDL
== References ==