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Conference proceeding
Systemization of Knowledge (SoK): Creating a Research Agenda for Human-Centered Real-Time Risk Detection on Social Media Platforms
CHI '24: Proceedings of the CHI Conference on Human Factors in Computing Systems, pp 1-21
May 2024
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Abstract
Accurate real-time risk identification is vital to protecting social media users from online harm, which has driven research towards advancements in machine learning (ML). While strides have been made regarding the computational facets of algorithms for “real-time” risk detection, such research has not yet evaluated these advancements through a human-centered lens. To this end, we conducted a systematic literature review of 53 peer-reviewed articles on real-time risk detection on social media. Real-time detection was mainly operationalized as “early” detection after-the-fact based on pre-defined chunks of data and evaluated based on standard performance metrics, such as timeliness. We identified several human-centered opportunities for advancing current algorithms, such as integrating human insight in feature selection, algorithms’ improvement considering human behavior, and utilizing human evaluations. This work serves as a critical call-to-action for the HCI and ML communities to work together to protect social media users before, during, and after exposure to risks.
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Details
- Title
- Systemization of Knowledge (SoK): Creating a Research Agenda for Human-Centered Real-Time Risk Detection on Social Media Platforms
- Creators
- Ashwaq Alsoubai - Vanderbilt UniversityJinkyung Katie Park - Vanderbilt UniversitySarvech Qadir - Vanderbilt UniversityGianluca Stringhini - Boston UniversityAfsaneh Razi (Corresponding Author) - Drexel University, Information Science (Informatics)Pamela J. Wisniewski - Vanderbilt University
- Publication Details
- CHI '24: Proceedings of the CHI Conference on Human Factors in Computing Systems, pp 1-21
- Conference
- CHI '24: CHI Conference on Human Factors in Computing Systems (Honolulu, HI, USA, 11 May 2024–16 May 2024)
- Publisher
- Association for Computing Machinery
- Number of pages
- 21
- Grant note
- U.S. National Science Foundation: IIP-2329976, IIS-2333207, CNS-1942610 William T. Grant Foundation: 187941
This research is supported in part by the U.S. National Science Foundation under grants #IIP-2329976, #IIS-2333207, #CNS-1942610 and by the William T. Grant Foundation grant #187941. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the research sponsors. We would also like to thank all the participants who donated their data and contributed to the research.
- Resource Type
- Conference proceeding
- Language
- English
- Academic Unit
- Information Science (Informatics)
- Web of Science ID
- WOS:001255317907038
- Scopus ID
- 2-s2.0-85194865488
- Other Identifier
- 991021874715304721
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- Collaboration types
- Domestic collaboration
- International collaboration
- Web of Science research areas
- Computer Science, Artificial Intelligence
- Computer Science, Information Systems
- Computer Science, Theory & Methods