Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Existing target-specific sentiment recognition methods consider only a single target per tet, and have been shown to miss nearly half of the actual targets mentioned.  present a corpus of UK election tets, with an average of 3.09 entities per tet and more than one type of sentiment in half of the tets. This requires a method for multi-target specific sentiment recognition, which  develop by using the context around a target as ll as syntactic dependencies involving the target.  present results of our method on both a benchmark corpus of single targets and the multi-target election corpus, showing state-of-the art performance in both corpora and outperforming previous approaches to multi-target sentiment task as ll as deep learning models for single-target sentiment.
['Bo Wang', 'Maria Liakata', 'Arkaitz Zubiaga', 'Rob Procter']
I am writing a research paper on a idea TDParse - multi-target-specific sentiment recognition on Twitter
[{"from": "human", "value": "I am writing a research paper on a idea TDParse - multi-target-specific sentiment recognition on Twitter"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Existing target-specific sentiment recognition methods consider only a single target per tet, and have been shown to miss nearly half of the actual targets mentioned.  present a corpus of UK election tets, with an average of 3.09 entities per tet and more than one type of sentiment in half of the tets. This requires a method for multi-target specific sentiment recognition, which  develop by using the context around a target as ll as syntactic dependencies involving the target.  present results of our method on both a benchmark corpus of single targets and the multi-target election corpus, showing state-of-the art performance in both corpora and outperforming previous approaches to multi-target sentiment task as ll as deep learning models for single-target sentiment."}]