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To elaborate the picture of credibility assessment by examining how participants of online discussion evaluate the informational credibility of conspiracy theories.
Abstract
Purpose
To elaborate the picture of credibility assessment by examining how participants of online discussion evaluate the informational credibility of conspiracy theories.
Design/methodology/approach
Descriptive quantitative analysis and qualitative content analysis of 2,663 posts submitted to seven Reddit threads discussing a conspiracy operation, that is, the damage of the Nord Stream gas pipelines in September 2022. It was examined how the participants of online discussion assess the credibility of information constitutive of conspiracy theories speculating about (1) suspected actors responsible for the damage, (2) their motives and (3) the ways in which the damage was made. The credibility assessments focussed on diverse sources offering information about the above three factors.
Findings
The participants assessed the credibility of information by drawing on four main criteria: plausibility of arguments, honesty in argumentation, similarity to one's beliefs and provision of evidence. Most assessments were negative and indicated doubt about the informational believability of conspiracy theories about the damage. Of the information sources referred to in the discussion, the posts submitted by fellow participants, television programmes and statements provided by governmental organizations were judged most critically, due to implausible argumentation and advocacy of biased views.
Research limitations/implications
As the study focuses on a sample of posts dealing with conspiracy theories about a particular event, the findings cannot be generalized to concern the informational credibility conspiracy narratives.
Originality/value
The study pioneers by providing an in-depth analysis of the nature of credibility assessments by focussing on information constitutive of conspiracy theories.
Details
Keywords
Yunfei Li, Shengbo Eben Li, Xingheng Jia, Shulin Zeng and Yu Wang
The purpose of this paper is to reduce the difficulty of model predictive control (MPC) deployment on FPGA so that researchers can make better use of FPGA technology for academic…
Abstract
Purpose
The purpose of this paper is to reduce the difficulty of model predictive control (MPC) deployment on FPGA so that researchers can make better use of FPGA technology for academic research.
Design/methodology/approach
In this paper, the MPC algorithm is written into FPGA by combining hardware with software. Experiments have verified this method.
Findings
This paper implements a ZYNQ-based design method, which could significantly reduce the difficulty of development. The comparison with the CPU solution results proves that FPGA has a significant acceleration effect on the solution of MPC through the method.
Research limitations implications
Due to the limitation of practical conditions, this paper cannot carry out a hardware-in-the-loop experiment for the time being, instead of an open-loop experiment.
Originality value
This paper proposes a new design method to deploy the MPC algorithm to the FPGA, reducing the development difficulty of the algorithm implementation on FPGA. It greatly facilitates researchers in the field of autonomous driving to carry out FPGA algorithm hardware acceleration research.
Details