Abstract
The increased reliance on user-generated content in the business models of online environments brings with it a challenge of setting up rules for content moderation. Namely, how should the firm create a fair and dynamic set of moderation guidelines that will be relevant and explainable? At present, firms are commonly setting the rules as they go and are in need to continuously assess, examine, and update with the help of content experts. Our work seeks to offer a different approach to generating content moderation rules in an economic, dynamic, and objective fashion. Specifically, we propose the use of crowdsourcing in symbiosis with NLP algorithms to compile and revise content moderation guidelines semi-automatically. We discuss how our proposed approach can be integrated into current moderation processes in practice.
Original language | English |
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Title of host publication | International Conference on Information Systems, ICIS 2020 - Making Digital Inclusive |
Subtitle of host publication | Blending the Local and the Global |
Publisher | Association for Information Systems |
ISBN (Electronic) | 9781733632553 |
State | Published - 2021 |
Event | 2020 International Conference on Information Systems - Making Digital Inclusive: Blending the Local and the Global, ICIS 2020 - Virtual, Online, India Duration: 13 Dec 2020 → 16 Dec 2020 |
Publication series
Name | International Conference on Information Systems, ICIS 2020 - Making Digital Inclusive: Blending the Local and the Global |
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Conference
Conference | 2020 International Conference on Information Systems - Making Digital Inclusive: Blending the Local and the Global, ICIS 2020 |
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Country/Territory | India |
City | Virtual, Online |
Period | 13/12/20 → 16/12/20 |
Bibliographical note
Publisher Copyright:© ICIS 2020. All rights reserved.
Keywords
- Content moderation
- Crowdsourcing
- Natural language processing
- User-generated content