A Language-based Approach to Measuring Scholarly Impact

Kevin Boyack kboyack at MAPOFSCIENCE.COM
Sat Oct 23 14:01:14 EDT 2010

>From Citeseer via GS lookup - PDF attached.

-----Original Message-----
From: ASIS&T Special Interest Group on Metrics
[mailto:SIGMETRICS at listserv.utk.edu] On Behalf Of David Wojick
Sent: Saturday, October 23, 2010 11:11 AM
To: SIGMETRICS at listserv.utk.edu
Subject: Re: [SIGMETRICS] A Language-based Approach to Measuring Scholarly

Sounds like something I have long wanted to try. Is there any contact 


At 08:42 PM 10/22/2010, you wrote:
>Adminstrative info for SIGMETRICS (for example unsubscribe):
>Interesting work, with nice results.
>Gerrish, S. M., EDU, P., & Blei, D. M. (2010). A Language-based Approach
>to Measuring Scholarly Impact. Presented at the 27th International
>Conference on Machine Learning (ICML 2010), Haifa, Israel.
>Abstract: Identifying the most influential documents in a corpus is an
>important problem in many fields, from information science and
>historiography to text summarization and news aggregation.
>Unfortunately, traditional bibliometrics such as citations are often not
>available. We propose using changes in the thematic content of documents
>over time to measure the importance of individual documents within the
>collection. We describe a dynamic topic model for both quantifying and
>qualifying the impact of these documents. We validate the model by
>analyzing three large corpora of scientific articles. Our measurement of
>a document's impact correlates significantly with its number of citations.
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