Attractiveness based conference ranking.

Conferences have a significant impact on the academic world. Academic conferences aim to exchange information about research results with others. The quality of the conference is highly considered because it involves the credibility of the research papers produced. Creating a ranking system is an effective way to measure conference quality and compare it with other venues. The existing conference ranking systems do not have a unified index or are still manually evaluated by humans, so there is a gap to create an academic conference evaluation system that is objective, comprehensive, and universal. To further improve the ranking system, we propose two new indicators in this work. In these two indicators, we quantify the attractiveness of conferences and combine them with the traditional three indicators to calculate the scores of 10 conferences in the field of data science through the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) model. The proposed new evaluation system can help authors understand conferences more comprehensively and screen conferences more sensibly.