Posted: October 9th, 2022

Types of Internet Portals, Examples and Income Revenue Models

Types of Internet Portals, Examples and Income Revenue Models

Internet Portal is a web designed to bring uniform information despite the diversity of the sources which a dedicated area page from information display depending on the preference of the user. It allows users to search intranet content without restricting domains. these portals offer different kinds of service which includes information from database, emails, daily news for some other uses they search for entertainment the portal collects information from different sources and presents in a symmetrical manner (Lotz, 2017).
There are two different types of portal, affinity portals and the focused content portals
Affinity portals
firstly, the affinity portal. in this type of portal, the users that use the portal have a common affinity that pushes them to get connected to that portal. it is a portal formed from shared interest where users can be formally or informally apart of, they can be portal based on friendships that allows users to engage and share ideas. in other cases, the users enjoy the services such as ecommerce, shopping and chat services (Du, 2019). For entertainment purposes the users can share photos among other social services an example of an affinity portal is Facebook, whereby is primary goal is for users to post and share information that is normally directed to many users with a common goal.
URL. http://www.facebook.com/
Focused- content portal
In this type of portal, it is collection of sites whose main focus is specific content, therefore the sites content in depth information relating a specific topic in which all the member users are interested in. in this portal, users with specific interest on certain content access the information from these portals, however the information is only limited to the company’s agenda without allowing for extra leverage information especially from outside sources. For essence users that are interested in gaming or weather, news or entertainment can search for the information from weather portals or gaming portal.
An example of the focused content portal is the rotten tomatoes website. the rotten tomato portal is only focused on specific content that is movie and series reviews. this is where movie and series fans and critics leave their reviews on the movies. this revies are openly visible to for users to view and in turn make decisions on whether to make movie purchase or not. The portal has allowance for TV shows, news tickets or show time and movies and DVDs. It further shows the available episode and movies that are available for purchase by users (Hoffman, 2016).
URL https://www.rottentomatoes.com/
Revenue income models
For Facebook, it obtains its revenues income through advertising revenue model. For example, in Facebook portal, it has a tag for ad hices.in some cases, it provides direct links to products or services that are advertise form the adverts. Additionally, it can offer direct marketing for users, however with a premium subscription after the registration (Hoffman, 2016).
For rotten tomatoes, just like Facebook, it gains ins revenue through advertisement. It has links to movies and films, and additional information for users for require that kind of access. through this it gains revenues from ads viewed during the information search and from the purchase of the movies and tv shows. in some case, they provide ticket purchases for concerts and in turn gains commission, Rotten tomatoes has integrated advertising model and is using it as an extra revenue income stream (Quader, 2017).

References
Du, P., Yu, S., & Yang, D. (2019). Online Services: Using Big Data to Create Intelligent Government Web Portals. In The Development of E-governance in China (pp. 87-112). Springer, Singapore.
Hoffman, A., & Gold, N. (2016). Facebook Inc.: Is its 100% Advertising Revenue Model Sustainable given the Rise of Mobile Ad-Blockers?.
Lotz, A. D. (2017). Portals: A treatise on internet-distributed television. Michigan Publishing, University of Michigan Library.
Quader, N., Gani, M. O., Chaki, D., & Ali, M. H. (2017, December). A machine learning approach to predict movie box-office success. In 2017 20th International Conference of Computer and Information Technology (ICCIT) (pp. 1-7). IEEE.

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