Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: ,  deal with the problem of predicting how much attention a newly submitted post would receive from fellow community members of closed communities in social networking sites. Though the concept of attention is subjective, the number of comments received by a post serves as a very good indicator of the same. Unlike previous work which primarily made use of either content features or the network features (friendship links on the network),  exploit both the content features and community level features (for instance, what time of the day is the community more active) for tackling this problem. Further,  focus on dedicated pages of corporate brands on social media bsites and accordingly extract important features from the content and community activity of such brand pages. The attention prediction task finds direct application in the listening, monitoring and engaging activities of the businesses that have such brand-pages. ,  formulate the problem of attention prediction on social media brand pages.    further propose Attention Prediction (AP) framework which integrates the various features that influence the attention received by a post using classification and regression based approaches. Experimental results on real world data extracted from some highly active brand pages on Facebook demonstrate the efficacy of the proposed framework.
['Himabindu Lakkaraju', 'Jitendra Ajmera']
I am writing a research paper on a idea Attention prediction on social media brand pages
[{"from": "human", "value": "I am writing a research paper on a idea Attention prediction on social media brand pages"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: ,  deal with the problem of predicting how much attention a newly submitted post would receive from fellow community members of closed communities in social networking sites. Though the concept of attention is subjective, the number of comments received by a post serves as a very good indicator of the same. Unlike previous work which primarily made use of either content features or the network features (friendship links on the network),  exploit both the content features and community level features (for instance, what time of the day is the community more active) for tackling this problem. Further,  focus on dedicated pages of corporate brands on social media bsites and accordingly extract important features from the content and community activity of such brand pages. The attention prediction task finds direct application in the listening, monitoring and engaging activities of the businesses that have such brand-pages. ,  formulate the problem of attention prediction on social media brand pages.    further propose Attention Prediction (AP) framework which integrates the various features that influence the attention received by a post using classification and regression based approaches. Experimental results on real world data extracted from some highly active brand pages on Facebook demonstrate the efficacy of the proposed framework."}]