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How is the use of AI in auditing perceived by auditors in social media ?

Pang Bei, Lu LU and Yan, Xiaoyu LU (2024) BUSN79 20241
Department of Business Administration
Abstract
Purpose: The purpose of this thesis is to critically evaluate posts/comments collected from
social media on AI auditing to analyze how auditors perceive the application of AI in the
auditing industry currently.
Methodology: We did qualitative research using content analysis to conduct our research. We
scraped posts/comments from Reddit, Quora, and Weibo for information collection purposes.
We used a paraphrasing approach for privacy concerns and we also used MAXQDA, which is
a qualitative and mixed methods academic research software, to analyze the data collected.
Theoretical perspectives: We analyzed the posts/comments from a perspective of epistemic
trust theory to understand how trust contributes to information sharing in... (More)
Purpose: The purpose of this thesis is to critically evaluate posts/comments collected from
social media on AI auditing to analyze how auditors perceive the application of AI in the
auditing industry currently.
Methodology: We did qualitative research using content analysis to conduct our research. We
scraped posts/comments from Reddit, Quora, and Weibo for information collection purposes.
We used a paraphrasing approach for privacy concerns and we also used MAXQDA, which is
a qualitative and mixed methods academic research software, to analyze the data collected.
Theoretical perspectives: We analyzed the posts/comments from a perspective of epistemic
trust theory to understand how trust contributes to information sharing in various social
settings.
Empirical foundation: To establish the empirical foundation, the data was collected by
scraping posts from social media from 2018 to 2024 regarding how auditors perceive AI
auditing. For a cross-cultural perspective, data that includes posts/comments was collected
from social platforms in different countries such as the US and China, and 163 valid
posts/comments were recognized after filtering certain keywords such as ‘AI’, ‘Audit’, and
‘Artificial intelligence”. For relevance and significance, we manually review the
posts/comments to refine our dataset. The research is based on qualitative content analysis
and it is conducted with MAXQDA, which is a qualitative and mixed method research
software.
Conclusions: Applying the concept of epistemic trust (McCraw, 2015) and doing content
analysis with posts/comments from social media provide us with a unique perspective on how
AI auditing is viewed by auditors. It was discovered that auditors have similar and some
different opinions as they are affected by various cultural factors. The main difference
between auditors with different cultural backgrounds is that auditors using Reddit and Quora
state that while AI can enhance auditing efficiency and accuracy in repetitive tasks, it cannot
replace auditors completely for its lack of professional judgment while others using Weibo
consider the replacement challenging as it cannot be held accountable for misjudgments. (Less)
Please use this url to cite or link to this publication:
author
Pang Bei, Lu LU and Yan, Xiaoyu LU
supervisor
organization
course
BUSN79 20241
year
type
H1 - Master's Degree (One Year)
subject
keywords
AI, Epistemic trust, Social media, Audit, AI Audit
language
English
id
9171957
date added to LUP
2024-08-20 16:44:15
date last changed
2024-08-20 16:44:15
@misc{9171957,
  abstract     = {{Purpose: The purpose of this thesis is to critically evaluate posts/comments collected from
social media on AI auditing to analyze how auditors perceive the application of AI in the
auditing industry currently.
Methodology: We did qualitative research using content analysis to conduct our research. We
scraped posts/comments from Reddit, Quora, and Weibo for information collection purposes.
We used a paraphrasing approach for privacy concerns and we also used MAXQDA, which is
a qualitative and mixed methods academic research software, to analyze the data collected.
Theoretical perspectives: We analyzed the posts/comments from a perspective of epistemic
trust theory to understand how trust contributes to information sharing in various social
settings.
Empirical foundation: To establish the empirical foundation, the data was collected by
scraping posts from social media from 2018 to 2024 regarding how auditors perceive AI
auditing. For a cross-cultural perspective, data that includes posts/comments was collected
from social platforms in different countries such as the US and China, and 163 valid
posts/comments were recognized after filtering certain keywords such as ‘AI’, ‘Audit’, and
‘Artificial intelligence”. For relevance and significance, we manually review the
posts/comments to refine our dataset. The research is based on qualitative content analysis
and it is conducted with MAXQDA, which is a qualitative and mixed method research
software.
Conclusions: Applying the concept of epistemic trust (McCraw, 2015) and doing content
analysis with posts/comments from social media provide us with a unique perspective on how
AI auditing is viewed by auditors. It was discovered that auditors have similar and some
different opinions as they are affected by various cultural factors. The main difference
between auditors with different cultural backgrounds is that auditors using Reddit and Quora
state that while AI can enhance auditing efficiency and accuracy in repetitive tasks, it cannot
replace auditors completely for its lack of professional judgment while others using Weibo
consider the replacement challenging as it cannot be held accountable for misjudgments.}},
  author       = {{Pang Bei, Lu and Yan, Xiaoyu}},
  language     = {{eng}},
  note         = {{Student Paper}},
  title        = {{How is the use of AI in auditing perceived by auditors in social media ?}},
  year         = {{2024}},
}