Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Online Social Networks (OSNs) such as Facebook and Twitter have become popular communication and information sharing tools for hundreds of millions of individuals in recent years. OSNs not only make people’s life more connected, but also attract the interest of spammers. Twitter spam generally contains deceptive information, such as “free voucher” and “ight loss advertisement” to attract the interest of victims. A comprehensive analysis on the deceptive information will be of great benefit to the detection of Twitter spam.  presents a study of deceptive information in Twitter spam. The analysis is based on a collection of over 550 million tets with around 6% spam.  find that various deceptive content of spam performs differently in luring victims to malicious sites.  also find the regional response rate to various Twitter spam outbreaks varies greatly. These two factors can contribute to improve the performance of spam detection techniques.
['Chao Chen', 'Sheng Wen', 'Jun Zhang', 'Yang Xiang', 'Jonathan Oliver', 'Abdulhameed Alelaiwi', 'Mohammad Mehedi Hassan']
I am writing a research paper on a idea Investigating the deceptive information in Twitter spam
[{"from": "human", "value": "I am writing a research paper on a idea Investigating the deceptive information in Twitter spam"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Online Social Networks (OSNs) such as Facebook and Twitter have become popular communication and information sharing tools for hundreds of millions of individuals in recent years. OSNs not only make people\u2019s life more connected, but also attract the interest of spammers. Twitter spam generally contains deceptive information, such as \u201cfree voucher\u201d and \u201cight loss advertisement\u201d to attract the interest of victims. A comprehensive analysis on the deceptive information will be of great benefit to the detection of Twitter spam.  presents a study of deceptive information in Twitter spam. The analysis is based on a collection of over 550 million tets with around 6% spam.  find that various deceptive content of spam performs differently in luring victims to malicious sites.  also find the regional response rate to various Twitter spam outbreaks varies greatly. These two factors can contribute to improve the performance of spam detection techniques."}]