Who funds this,who employs me, where the data came from.
Research on AI trust is worth less if you cannot see who is behind it. Everything that could reasonably be read as a competing interest is on this page.
Affiliations
| Employment | Regional Vice President, Revenue, Southeast Asia, Isentia. Isentia is a media intelligence and social listening company operating across Asia-Pacific, part of Pulsar Group. This is a full-time commercial role and it is the author’s primary employment. |
|---|---|
| Doctoral research | PhD researcher, Wee Kim Wee School of Communication and Information, Nanyang Technological University, Singapore. All six studies in the programme are written with Andrew Prahl at NTU. |
| Teaching | Adjunct faculty at ESSEC Business School and SP Jain School of Global Management. Mentor at Founder Institute. |
| Identifiers | ORCID 0009-0006-2524-5006 · Google Scholar |
Independence of this site
This is a personal research site. It is not an Isentia publication, it is not reviewed or approved by Isentia, and nothing on it should be read as an Isentia position. Views are the author’s own. The same applies to Nanyang Technological University, ESSEC and SP Jain.
The site sells nothing. It carries no advertising, no affiliate links and no sponsored content. Commercial media intelligence enquiries are routed to Isentia rather than handled personally — see Practice.
Competing interests
The author holds a commercial revenue role at a media intelligence and social listening company while publishing research on AI personas, disclosure and social media behaviour. These are adjacent domains. Readers, reviewers and editors should weigh the research with that in mind, which is why it is stated plainly here rather than left to be discovered.
Funding
No employer and no client has funded, commissioned, reviewed or approved any study in this programme. The research is conducted as doctoral work at Nanyang Technological University and carries no commercial sponsorship. Nothing on this site is paid placement.
Data provenance
Each study states its data sources in full in the published paper. In summary, the programme draws on two kinds of material and no others:
- Published academic literature. The threshold model is built from a systematic map of 2,685 articles and 111 AI-persona studies, all publicly available scholarship.
- Publicly posted social media content. Instagram posts, public comment threads, forum discussions, app-store reviews and similar material that any member of the public can read without an account, credential or licence.
No confidential data is used anywhere in the programme. No client data, and no data identifying any client of any employer, appears in any study or on this site. No individual is named. Where the research reports counts — 1,531 Instagram posts, 3,670 posts and reviews, 8,139 items coded by hand — those refer to public posts, not to customers, panels or client records.
Corrections
Publication statuses on this site change as manuscripts move. If something here is out of date or wrong, write to the address in the footer and it will be corrected and re-dated. Last reviewed 2026-07-27.