Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: ,  propose a method for classifying Twitter accounts into non-targeting accounts, which post messages to the general public, and targeting accounts, which post messages to specific people. For example, an account posting general news information is a non-targeting account, while an account posting announcements to members of a specific organization is a targeting account. An account posting information on very specific minor topic, and an account used for communication with friends, are also targeting accounts. Our method finds some properties that are common to most follors of a given account, and calculate how much a user set with such a consistency deviates from a random sample from the given universe of users (e.g., the set of all Twitter users in some country). If it largely deviates, the account is a targeting account.  use two types of properties of follors: (1) terms in their metadata and (2) their folloes. The result of our experiment shows that one of our methods, which computes two scores based on these two types of properties and combines them using SVM, achieves the accuracy 0.944, and outperforms the baselines.
['Hikaru Takemura', 'Keishi Tajima']
I am writing a research paper on a idea Classification of Twitter Accounts into Targeting Accounts and Non-Targeting Accounts
[{"from": "human", "value": "I am writing a research paper on a idea Classification of Twitter Accounts into Targeting Accounts and Non-Targeting Accounts"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: ,  propose a method for classifying Twitter accounts into non-targeting accounts, which post messages to the general public, and targeting accounts, which post messages to specific people. For example, an account posting general news information is a non-targeting account, while an account posting announcements to members of a specific organization is a targeting account. An account posting information on very specific minor topic, and an account used for communication with friends, are also targeting accounts. Our method finds some properties that are common to most follors of a given account, and calculate how much a user set with such a consistency deviates from a random sample from the given universe of users (e.g., the set of all Twitter users in some country). If it largely deviates, the account is a targeting account.  use two types of properties of follors: (1) terms in their metadata and (2) their folloes. The result of our experiment shows that one of our methods, which computes two scores based on these two types of properties and combines them using SVM, achieves the accuracy 0.944, and outperforms the baselines."}]