| Abstract: | Twitter has become a prolific social media platform where influential people like TV celebrities, politicians, and athletes, as well as ordinary people, can put forward their opinion on various topics in the form of tweet. At the end of every tweet, people use hashtags to index keywords or topics in the platform. In this project, we are developing a web-app named Tweeter, where we suggest hashtags based on the content of the tweet. For this, we are developing a web-interface where users can type a tweet. On the side, the system will suggest relevant hashtags. We will be using Twitter API where we can access Twitter data and gather various trending hashtags. When users type their tweets, the app analyzes the contents of the tweet and after processing them and scanning the data from Twitter API, relevant hashtags are suggested. For such actions, we use algorithms like machine learning and natural language processing to gather relevant hashtags from the tweet itself and other related trending hashtags. We will use cloud technology for all database and back end data processing. |