Now a day’s millions of people use social networks like Facebook and Twitter to communicate, showing present status, achievements, and daily activities. Like two sides for a coin, here also two different paths that affect human life negatively and positively by the usage of social networks in the present world, like a genuine users some fake users spread fake contents by using fake user identities that may lead to several problems in the society like law and order problems, riots, protests, etc… to avoid these type of actions nowadays researchers focuses on spam detection techniques in twitter by which results are getting positively. Researchers employed spam-detection methods that relied on phoney users, spam-based URLs, spamming of popular topics, and fake material. All these techniques work based on features available on social networks like user information, content sharing, graphical data, time and structural data. Present literature work in this paper gives deep information about different techniques used by researchers to detect spam contents in various social networks that may be useful for researchers to have information gathered in a spot.