Machine Learning in Online Social Network

An online social network (OSN) is a social structure Machine Learning in Online Social Network “The primary aim is to allow the computers learn automatically without human intervention or assistance and adjust actions accordingly.” provides systems the ability to automatically learn and improve from experience without being
explicitly programmed . Machine learning focuses on the development of computer programs that can access data and use it learn for themselves . The process of learning begins with observations or data , such as examples , direct experience , or instruction , in order to look for patterns in data and make better decisions in the future based on the examples that we provide . The primary aim is to allow the computers learn automatically without human intervention or assistance and adjust actions accordingly . Back in the day, Bebo, MySpace and then Facebook”were
fun tools to find events , share photos and chat with friends, but communicating with brands required picking up the phone , sending ” emails or visiting the company website to get the information you needed . Nowadays , it couldn ’t be more different . 95 percent of users expect to engage with brands like face book, made “up of individuals or organization s th at can be called as “nodes ” , and the links which are the different types of interdependence relationship between nodes . In fact , a social network is based on two parameters : nodes and links . The nodes define the content of the relationships ( links ) according to their theme / interest /attendance (e.g. trade financial , friendship, dislike, trade” ” , sexual relations, disease transmission ( epidemiology ). An important attribute of a link is the type of information exchange / communication technology ( e . g . using mobile equipment). Today social networks use web – based services , so the type of communication can modify the behaviour of nodes the communication habits of OSN users . machine learning is and application of artificial intelligence (AI) that” twitter , and 42 percent of brand marketers state that Facebook is critical to their day -to- day business . With users leaving more than 1.5 million pieces of user-generated content on Facebook each day , companies are leaning on
new technology to help them manage huge numbers of conversations in a time – effective manner. One of the most important new tech trends for social media managers is machine learning / artificial intelligence. In the age of big data , brands ” now have access to more information than ever about their customer base . One of the main challenges of social media marketing is segmentation — targeting people with content that they are interested in based on their “online activity and demographics . Using a mix of big data analysis and machine learning, brands can effectively target users with messaging in a language they really under stand and push offers , deals and ads that appeal to them across a range of channels.