Thesis
Infostratus: incentivized information rating in a decentralized trust network
Master of Science (M.S.), Drexel University
Dec 2021
DOI:
https://doi.org/10.17918/00000911
Abstract
In recent years, the rising use of social media has produced concerns over the formation of social echo chambers that would have been largely impossible without such large-scale interconnectedness. The platforms that host our daily interactions have recently fallen under considerable criticism for varying levels of censorship on one end of the spectrum, or for allowing blatant misinformation and disinformation on the other. This raises the problem of information validation. Under the current system, it falls to the members of the network themselves to handle determining the veracity of information reaching them through the network, or to determine what fact checkers they should trust through their own knowledge. This, of course, has its own challenges - with the sheer volume of information on the Internet, much of it directly contradictory, the task of sifting through it is no simple task. In this paper, we shall outline a layered consensus mechanism which may be applied on top of a decentralized network to distribute the fact-checking process to a large number of individuals. Our final goal will be to construct an incentive scheme which leads to a marked improvement in the accuracy of the network's ratings.
Metrics
46 File views/ downloads
46 Record Views
Details
- Title
- Infostratus
- Creators
- Sean Thomas Batzel
- Contributors
- Emmanouil Pountourakis (Advisor)
- Awarding Institution
- Drexel University
- Degree Awarded
- Master of Science (M.S.)
- Publisher
- Drexel University; Philadelphia, Pennsylvania
- Number of pages
- viii, 171 pages
- Resource Type
- Thesis
- Language
- English
- Academic Unit
- Computer Science (Computing) (2013-2026); College of Computing and Informatics (2013-2026); Drexel University
- Other Identifier
- 991016456058804721