Details
| Original language | English |
|---|---|
| Title of host publication | WWW '22 |
| Subtitle of host publication | Proceedings of the ACM Web Conference 2022 |
| Pages | 2646-2656 |
| Number of pages | 11 |
| ISBN (electronic) | 9781450390965 |
| Publication status | Published - 25 Apr 2022 |
| Event | 31st ACM World Wide Web Conference, WWW 2022 - Virtual, Online, France Duration: 25 Apr 2022 → 29 Apr 2022 |
Abstract
Recently, almost all conferences have moved to virtual mode due to the pandemic-induced restrictions on travel and social gathering. Contrary to in-person conferences, virtual conferences face the challenge of efficiently scheduling talks, accounting for the availability of participants from different timezones and their interests in attending different talks. A natural objective for conference organizers is to maximize efficiency, e.g., total expected audience participation across all talks. However, we show that optimizing for efficiency alone can result in an unfair virtual conference schedule, where individual utilities for participants and speakers can be highly unequal. To address this, we formally define fairness notions for participants and speakers, and derive suitable objectives to account for them. As the efficiency and fairness objectives can be in conflict with each other, we propose a joint optimization framework that allows conference organizers to design schedules that balance (i.e., allow trade-offs) among efficiency, participant fairness and speaker fairness objectives. While the optimization problem can be solved using integer programming to schedule smaller conferences, we provide two scalable techniques to cater to bigger conferences. Extensive evaluations over multiple real-world datasets show the efficacy and flexibility of our proposed approaches.
Keywords
- Fair Conference Scheduling, Virtual Conference Scheduling
ASJC Scopus subject areas
- Computer Science(all)
- Computer Networks and Communications
- Computer Science(all)
- Software
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WWW '22: Proceedings of the ACM Web Conference 2022. 2022. p. 2646-2656.
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - Scheduling Virtual Conferences Fairly
T2 - 31st ACM World Wide Web Conference, WWW 2022
AU - Patro, Gourab K.
AU - Jana, Prithwish
AU - Chakraborty, Abhijnan
AU - Gummadi, Krishna P.
AU - Ganguly, Niloy
N1 - Funding Information: This research has been supported by the National Key R&D Program of China under Grant No. 2020AAA0106600, the National Natural Science Foundation of China under Grant Nos. 62176014, U1836206.
PY - 2022/4/25
Y1 - 2022/4/25
N2 - Recently, almost all conferences have moved to virtual mode due to the pandemic-induced restrictions on travel and social gathering. Contrary to in-person conferences, virtual conferences face the challenge of efficiently scheduling talks, accounting for the availability of participants from different timezones and their interests in attending different talks. A natural objective for conference organizers is to maximize efficiency, e.g., total expected audience participation across all talks. However, we show that optimizing for efficiency alone can result in an unfair virtual conference schedule, where individual utilities for participants and speakers can be highly unequal. To address this, we formally define fairness notions for participants and speakers, and derive suitable objectives to account for them. As the efficiency and fairness objectives can be in conflict with each other, we propose a joint optimization framework that allows conference organizers to design schedules that balance (i.e., allow trade-offs) among efficiency, participant fairness and speaker fairness objectives. While the optimization problem can be solved using integer programming to schedule smaller conferences, we provide two scalable techniques to cater to bigger conferences. Extensive evaluations over multiple real-world datasets show the efficacy and flexibility of our proposed approaches.
AB - Recently, almost all conferences have moved to virtual mode due to the pandemic-induced restrictions on travel and social gathering. Contrary to in-person conferences, virtual conferences face the challenge of efficiently scheduling talks, accounting for the availability of participants from different timezones and their interests in attending different talks. A natural objective for conference organizers is to maximize efficiency, e.g., total expected audience participation across all talks. However, we show that optimizing for efficiency alone can result in an unfair virtual conference schedule, where individual utilities for participants and speakers can be highly unequal. To address this, we formally define fairness notions for participants and speakers, and derive suitable objectives to account for them. As the efficiency and fairness objectives can be in conflict with each other, we propose a joint optimization framework that allows conference organizers to design schedules that balance (i.e., allow trade-offs) among efficiency, participant fairness and speaker fairness objectives. While the optimization problem can be solved using integer programming to schedule smaller conferences, we provide two scalable techniques to cater to bigger conferences. Extensive evaluations over multiple real-world datasets show the efficacy and flexibility of our proposed approaches.
KW - Fair Conference Scheduling
KW - Virtual Conference Scheduling
UR - http://www.scopus.com/inward/record.url?scp=85129847954&partnerID=8YFLogxK
U2 - 10.48550/arXiv.2204.12062
DO - 10.48550/arXiv.2204.12062
M3 - Conference contribution
AN - SCOPUS:85129847954
SP - 2646
EP - 2656
BT - WWW '22
Y2 - 25 April 2022 through 29 April 2022
ER -