Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Location-sharing services such as Facebook and Foursquare/Swarm have become increasingly popular, due to the ease at which users can share their locations, and participate in services, games and other applications that leverage these locations. But it is important for people who use these services to configure appropriate location-privacy preferences so that they can control to whom they want to share their location information. Manually configuring these preferences may be burdensome and confusing, and so location-privacy preference recommenders based on crowdsourcing preferences from other users have been proposed. Whether people will accept the recommended preferences acquired from other users, who they may not know or trust, has not, hover, been investigated. ,  present a user experiment (n=99) to explore what factors influence people's acceptance of location-privacy preference recommenders.  find that 44% of our participants have privacy concerns about such recommenders. These concerns are shown to have a negative effect (p
['Yuchen Zhao', 'Juan Ye', 'Tristan Henderson']
I am writing a research paper on a idea The Effect of Privacy Concerns on Privacy Recommenders
[{"from": "human", "value": "I am writing a research paper on a idea The Effect of Privacy Concerns on Privacy Recommenders"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Location-sharing services such as Facebook and Foursquare/Swarm have become increasingly popular, due to the ease at which users can share their locations, and participate in services, games and other applications that leverage these locations. But it is important for people who use these services to configure appropriate location-privacy preferences so that they can control to whom they want to share their location information. Manually configuring these preferences may be burdensome and confusing, and so location-privacy preference recommenders based on crowdsourcing preferences from other users have been proposed. Whether people will accept the recommended preferences acquired from other users, who they may not know or trust, has not, hover, been investigated. ,  present a user experiment (n=99) to explore what factors influence people's acceptance of location-privacy preference recommenders.  find that 44% of our participants have privacy concerns about such recommenders. These concerns are shown to have a negative effect (p"}]