Collective citation analysis using Google Scholar
Citation analysis has historically been a metric for evaluation of a scientist or researcher’s academic contribution. There are reputed sources such as Google Scholar and Scopus which provide citation statistics for researchers which are further used to develop an unbiased score or view of their wor...
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| Format: | Final Year Project (FYP) |
| Language: | English |
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2015
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| Online Access: | http://hdl.handle.net/10356/62852 |
| _version_ | 1826123068773236736 |
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| author | Chemburkar, Nishant |
| author2 | He Bingsheng |
| author_facet | He Bingsheng Chemburkar, Nishant |
| author_sort | Chemburkar, Nishant |
| collection | NTU |
| description | Citation analysis has historically been a metric for evaluation of a scientist or researcher’s academic contribution. There are reputed sources such as Google Scholar and Scopus which provide citation statistics for researchers which are further used to develop an unbiased score or view of their work. There is, however, a need for a system which is able to calculate and present academic metrics for a group of scientists or researchers on the basis of their academic contribution. This report presents a solutions which has been developed to achieve the same. The system developed retrieves and calculates collective metrics for a group of researchers and is also able to store relationships between researchers, departments and universities, which allow the user to view and calculate metrics on the basis of locations, institutions, departments and sub departments. The system sources its raw data from Google Scholar and calculates additional metrics based on the citations retrieved. It generates popular metrics such has h-index, g-index, i-10 index and also presents experimental metrics such as collective h-index and g-index. It also provides additional statistics such as the averages and the leaderboards for that group of authors. This report uses a group of departments from Nanyang Technological University, Singapore to present the results of the application. In particular, the raw data from professors from School of Computer Engineering, was used to calculate the collective statistics and preserve the sub-department relations. The system has been developed to provide both a command line and a graphical user interface for a user to interact with the system. The author has recommended a future implementation of the system, which is able to fetch data regarding the researcher-institute-location information intelligently and proceed to calculate the collective citation analysis. |
| first_indexed | 2024-10-01T05:58:35Z |
| format | Final Year Project (FYP) |
| id | ntu-10356/62852 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T05:58:35Z |
| publishDate | 2015 |
| record_format | dspace |
| spelling | ntu-10356/628522023-03-03T20:47:35Z Collective citation analysis using Google Scholar Chemburkar, Nishant He Bingsheng School of Computer Engineering DRNTU::Engineering::Computer science and engineering Citation analysis has historically been a metric for evaluation of a scientist or researcher’s academic contribution. There are reputed sources such as Google Scholar and Scopus which provide citation statistics for researchers which are further used to develop an unbiased score or view of their work. There is, however, a need for a system which is able to calculate and present academic metrics for a group of scientists or researchers on the basis of their academic contribution. This report presents a solutions which has been developed to achieve the same. The system developed retrieves and calculates collective metrics for a group of researchers and is also able to store relationships between researchers, departments and universities, which allow the user to view and calculate metrics on the basis of locations, institutions, departments and sub departments. The system sources its raw data from Google Scholar and calculates additional metrics based on the citations retrieved. It generates popular metrics such has h-index, g-index, i-10 index and also presents experimental metrics such as collective h-index and g-index. It also provides additional statistics such as the averages and the leaderboards for that group of authors. This report uses a group of departments from Nanyang Technological University, Singapore to present the results of the application. In particular, the raw data from professors from School of Computer Engineering, was used to calculate the collective statistics and preserve the sub-department relations. The system has been developed to provide both a command line and a graphical user interface for a user to interact with the system. The author has recommended a future implementation of the system, which is able to fetch data regarding the researcher-institute-location information intelligently and proceed to calculate the collective citation analysis. Bachelor of Engineering (Computer Science) 2015-04-30T02:53:23Z 2015-04-30T02:53:23Z 2015 2015 Final Year Project (FYP) http://hdl.handle.net/10356/62852 en Nanyang Technological University 52 p. application/pdf |
| spellingShingle | DRNTU::Engineering::Computer science and engineering Chemburkar, Nishant Collective citation analysis using Google Scholar |
| title | Collective citation analysis using Google Scholar |
| title_full | Collective citation analysis using Google Scholar |
| title_fullStr | Collective citation analysis using Google Scholar |
| title_full_unstemmed | Collective citation analysis using Google Scholar |
| title_short | Collective citation analysis using Google Scholar |
| title_sort | collective citation analysis using google scholar |
| topic | DRNTU::Engineering::Computer science and engineering |
| url | http://hdl.handle.net/10356/62852 |
| work_keys_str_mv | AT chemburkarnishant collectivecitationanalysisusinggooglescholar |