Craggs, Barnaby and Rashid, Awais and Chiasson, Mike (2017) Information bias and trust in bitcoin speculation. PhD thesis, Lancaster University.
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Abstract
The Internet pervades modern life, offering up opportunities to connect, inform and be informed. As the range and number of sources for information online explode, how people select and interpret information has become a pertinent area for study, not least in light of the prevalence of fake-news. People are well known to act upon information they believe to be trustworthy and where the decision to act incurs risk, an inability to accurately select and assess the credibility of information presents a challenge. Bitcoin, the nascent crypto-currency, presents a domain within which profound financial risk abounds. Even for those armed with experience and knowledge there are numerous challenges to assessing risk, especially as sources of Bitcoin information can be observed to be partisan and of questionable accuracy. Within the domain of bitcoin speculation, this thesis asks the central research question of: are people able to select and correctly evaluate information they might rely upon to make decisions? In addressing this research question, this thesis offers - through the application of a psychological model of informational trust to bitcoin speculators - two fundamental contributions: Firstly, that these users are able to identify relevant news without a reliance upon confirmation bias. Secondly, that a notable percentage of users are not evaluating the credibility of online news by expertly interpreting the fundamentals of information but, rather deferring their trust to either the source news website or a more broad trust of information on the Internet. For these users, chance or luck may mean that they are basing their decisions upon factually accurate news. But this is a position which makes them particularly vulnerable to fake-news where it is spread via sources which they might trust. This position of susceptibility provides evidence to support further security research of both the prevalence of, and counter-measures for fake-news.