Recently, the Internet usage spread in all areas of life. Online news is among the popular articles on the Internet, which occupies a large portion of online information. The online news will be viewed almost every second in order to follow the evolution of any desired global events. There are many organizations or political parties employ agents for tracking news by grouping the event. Therefore, news clustering is helpful and worthy for many researchers and online news readers in order to view events from multiple perspectives. Additionally, it can be used in online news summarization, topic detection and tracking for extracting and detecting new events or topics in the news articles. The news extraction can be applied on news articles in the form of monolingual or multilingual. On the other hand, news aggregation is the most important method for scrawling and collecting events based on topics or categorization. This paper investigates the challenges and issues that relate to online news research. The discussions include the overview of system architectures, online news techniques, and a few related computer applications for the above mentioned online news areas.