Buttliere, B: Identifying high impact scientific work using Natural Language Processing and Psychology

In response to: Whalen, R., Huang, Y., Sawant, A., Uzzi, B. & Contractor, N.: Natural Language Processing, Article Content & Bibliometrics: Predicting High Impact Science

Abstract: The target article and this response focus on utilizing the available information about papers (e.g., full text, citations, mentions and discussion elsewhere on the internet) to better inform our understanding of the work’s impact on the field. Whalen, Huang, Sawant, Uzzi, & Contractor (2015) found evidence that especially the number of citations from papers that utilize highly dissimilar keywords was related to more citations outside of the journal. In our response, we reply to the major aspects of their paper and suggest two further things for potential discussion.

License: Creative Commons Attribution 4.0 International (CC-BY 4.0)

File: ASCW15_buttliere_response_whalen-etal.pdf

Leave a Reply

Your email address will not be published. Required fields are marked *

ascw Captcha ensure human user * Time limit is exhausted. Please reload the CAPTCHA.