1. Gouri Ginde 1, Snehanshu Saha 1, Chitra Balasubramaniam 2, Harsha R.S 2, Archana Mathur 3, BS Dayasagar 4, Anand M N 5 1,2,3 Department of Computer Science and Engineering PESIT South Campus Bangalore 4 SSIU, ISI Bangalore, 5 BITS Hyderabad 1 snehanshusaha@pes.edu, 1 gouri.ginde@gmail.com, 2 chitra2793@gmail.com 2 harshars89@gmail.com, 3 archanamathur@pes.edu, 4 bsdsagar@isibang.ac.in 5 anandmn1@gmail.com Mining massive databases for computation of scholastic indices - Model and Quantify ‘internationality’ of peer-reviewed journals

2. C ONTENTS Introduction Problem definition Solution Approach and Algorithms Results Conclusion and Future work 2

3. I NTRODUCTION Various authors and research scholars in recent times have been exploring means to find the reputed journals for publication of their articles. The drive behind this is to own appreciation/award for the quality work they do. Also institutional assessment and evaluation depends heavily on the peer reviewed publications irrespective of academia or research labs. The basic tendency is to publish their research in journals with an ‘international’ tag attached to it. 3

4. P ROBLEM AND O UR S OLUTION 4  There exists no metric to rank journals based on the extent or scale of internationality.  An absolute necessity to evaluate rank categorize journals based on internationality. validate the credibility of an “International” tag associated with any journal  Define ‘internationality’ as a metric, set qualitative benchmarks, define and quantify ‘new’ predictor variables.  Model ‘internationality’ as a score; rank and cluster journals according to ‘granules of internationality’.  Provide a calculator like tool to readily compute this new metric

5. 5 Dimensionality Analysis Feature Extraction & Data Collection Total Cited documents International Collaboration Ratio SNIP Self Citation Analytics : Cobb-Douglas Log Production Model Google Scholar Used Inspect element tool Beautiful Parser Web Scraping to get Journal Names Classification and Clustering End result is Clusters S UMMARY OF THE “I NTERNATIONALITY ” CALCULATION P ROCESS

6. A LGORITHM TO EXTRACT JOURNAL NAMES Algorithm: Input: A html file of webpage - (HLINK) (https://scholar.google.co.in/citations?view_op=top_venues& hl=en&vq=eng)https://scholar.google.co.in/citations?view_op=top_venues& hl=en&vq=eng Output: List of 1160 Journal Names 1. For every hyper link in this.html: HLINK 2. For every hyperlink in the HLINK webpage 3. Print gs_title from tag to spreadsheet 6 Journal Name 1 AAAI Conference on Artificial Intelligence … ……………. 722 Journal of Educational Computing Research.. 1042 Social Network Analysis and Mining 1043 Soft Computing

7. C OMPUTATION OF THE S ELF - CITATION Self-citation : A paper S is considered a self-citation of P, if P and S share at least one author. Check self-citations by comparison of the author's textual names. Algorithm to compute self citations: Input: List of Journal Names (J) from GS Output: Self-citation count for each paper(P) in J 1. For every Journal: J 2. For every paper: P 3. Get all the citing papers: X[ ] 4. For every paper X[i] 5. If P.author_name in X[i].author_names 6. Then 7. IncrByOne(J.SelfCitationCount) 7

8. RESULTS: 8 For all publications between 2012 and 2015

9. C ONCLUSION Try to quantify “internationality” of Journals. Provide a shape of “internationality” country wise; which essentially means providing a shape to the prestige of countries in publishing international journals. 9 F UTURE W ORK Scrape the GS for author affiliations to get the international collaboration ratio Calculate the SNIP Create a calculator like user interface to compute the Internationality of the input Journal name

10. Thank you 10