Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  analyze the online response to the preprint publication of a cohort of 4,606 scientific articles submitted to the preprint database arXiv.org beten October 2010 and May 2011.  study three forms of responses to these preprints: downloads on the arXiv.org site, mentions on the social media site Twitter, and early citations in the scholarly record.  perform two analyses. First,  analyze the delay and time span of article downloads and Twitter mentions following submission, to understand the temporal configuration of these reactions and whether one precedes or follows the other. Second,  run regression and correlation tests to investigate the relationship beten Twitter mentions, arXiv downloads, and article citations.  find that Twitter mentions and arXiv downloads of scholarly articles follow two distinct temporal patterns of activity, with Twitter mentions having shorter delays and narror time spans than arXiv downloads.  also find that the volume of Twitter mentions is statistically correlated with arXiv downloads and early citations just months after the publication of a preprint, with a possible bias that favors highly mentioned articles.
['Xin Shuai', 'Alberto Pepe', 'Johan Bollen']
I am writing a research paper on a idea How the Scientific Community Reacts to Newly Submitted Preprints: Article Downloads, Twitter Mentions, and Citations
[{"from": "human", "value": "I am writing a research paper on a idea How the Scientific Community Reacts to Newly Submitted Preprints: Article Downloads, Twitter Mentions, and Citations"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  analyze the online response to the preprint publication of a cohort of 4,606 scientific articles submitted to the preprint database arXiv.org beten October 2010 and May 2011.  study three forms of responses to these preprints: downloads on the arXiv.org site, mentions on the social media site Twitter, and early citations in the scholarly record.  perform two analyses. First,  analyze the delay and time span of article downloads and Twitter mentions following submission, to understand the temporal configuration of these reactions and whether one precedes or follows the other. Second,  run regression and correlation tests to investigate the relationship beten Twitter mentions, arXiv downloads, and article citations.  find that Twitter mentions and arXiv downloads of scholarly articles follow two distinct temporal patterns of activity, with Twitter mentions having shorter delays and narror time spans than arXiv downloads.  also find that the volume of Twitter mentions is statistically correlated with arXiv downloads and early citations just months after the publication of a preprint, with a possible bias that favors highly mentioned articles."}]