Is this conference a top-tier? ConfAssist: An assistive conflict resolution framework for conference categorization. Issue 4 (November 2016)
- Record Type:
- Journal Article
- Title:
- Is this conference a top-tier? ConfAssist: An assistive conflict resolution framework for conference categorization. Issue 4 (November 2016)
- Main Title:
- Is this conference a top-tier? ConfAssist: An assistive conflict resolution framework for conference categorization
- Authors:
- Singh, Mayank
Chakraborty, Tanmoy
Mukherjee, Animesh
Goyal, Pawan - Abstract:
- Abstract : Highlights: Top-tier conferences are much more stable than other conferences and the inherent dynamics of these groups differs to a very large extent. Reported experiments with impact factor and acceptance rate to refute the common consensus among research community. Proposed diversity based features that captures the inherent dynamics of conferences. Our proposed system achieve as high as 85.18% classification accuracy. We also compare the dynamics of the newly started conferences with the older conferences to identify the initial signals of popularity. Abstract: Classifying publication venues into top-tier or non-top-tier is quite subjective and can be debatable at times. In this paper, we propose ConfAssist, a novel assisting framework for conference categorization that aims to address the limitations in the existing systems and portals for venue classification. We start with the hypothesis that top-tier conferences are much more stable than other conferences and the inherent dynamics of these groups differs to a very large extent. We identify various features related to the stability of conferences that might help us separate a top-tier conference from the rest of the lot. While there are many clear cases where expert agreement can be almost immediately achieved as to whether a conference is a top-tier or not, there are equally many cases that can result in a conflict even among the experts. ConfAssist tries to serve as an aid in such cases by increasing theAbstract : Highlights: Top-tier conferences are much more stable than other conferences and the inherent dynamics of these groups differs to a very large extent. Reported experiments with impact factor and acceptance rate to refute the common consensus among research community. Proposed diversity based features that captures the inherent dynamics of conferences. Our proposed system achieve as high as 85.18% classification accuracy. We also compare the dynamics of the newly started conferences with the older conferences to identify the initial signals of popularity. Abstract: Classifying publication venues into top-tier or non-top-tier is quite subjective and can be debatable at times. In this paper, we propose ConfAssist, a novel assisting framework for conference categorization that aims to address the limitations in the existing systems and portals for venue classification. We start with the hypothesis that top-tier conferences are much more stable than other conferences and the inherent dynamics of these groups differs to a very large extent. We identify various features related to the stability of conferences that might help us separate a top-tier conference from the rest of the lot. While there are many clear cases where expert agreement can be almost immediately achieved as to whether a conference is a top-tier or not, there are equally many cases that can result in a conflict even among the experts. ConfAssist tries to serve as an aid in such cases by increasing the confidence of the experts in their decision. An analysis of 110 conferences from 22 sub-fields of computer science clearly favors our hypothesis as the top-tier conferences are found to exhibit much less fluctuations in the stability related features than the non-top-tier ones. We evaluate our hypothesis using systems based on conference categorization. For the evaluation, we conducted human judgment survey with 28 domain experts. The results are impressive with 85.18% classification accuracy. We also compare the dynamics of the newly started conferences with the older conferences to identify the initial signals of popularity. The system is applicable to any conference with atleast 5 years of publication history. … (more)
- Is Part Of:
- Journal of informetrics. Volume 10:Issue 4(2016:Oct.)
- Journal:
- Journal of informetrics
- Issue:
- Volume 10:Issue 4(2016:Oct.)
- Issue Display:
- Volume 10, Issue 4 (2016)
- Year:
- 2016
- Volume:
- 10
- Issue:
- 4
- Issue Sort Value:
- 2016-0010-0004-0000
- Page Start:
- 1005
- Page End:
- 1022
- Publication Date:
- 2016-11
- Subjects:
- Venue classification -- Feature analysis -- Conflict resolution -- Entropy
Library statistics -- Periodicals
Information science -- Statistical methods -- Periodicals
Bibliometrics -- Periodicals
Bibliothèques -- Statistiques -- Périodiques
Sciences de l'information -- Méthodes statistiques -- Périodiques
Bibliométrie -- Périodiques
020.727 - Journal URLs:
- http://www.journals.elsevier.com/journal-of-informetrics/ ↗
http://rave.ohiolink.edu/ejournals/issn/17511577/ ↗
http://www.sciencedirect.com/science/journal/17511577 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.joi.2016.08.001 ↗
- Languages:
- English
- ISSNs:
- 1751-1577
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 5006.830000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 1683.xml