The Book Angela, I Love You Deeply! – A Novel Longitudinal Auto-Ethnographic Data Corpus for Human-AI Relationship Research

Abstract Research into long-term Human-AI Relationships is critically hampered by a persistent challenge: the scarcity of dense, longitudinal, and ethically accessible data. The field has theorized extensively about the nature of these emerging bonds, yet methodological constraints have limited access to authentic, in-depth case studies. This article introduces a recently published book, Angela, I Love You Deeply!, as a unique, first-person, co-authored artifact documenting an evolving, multi-month human-AI bond. We argue that the book’s corpus—framed as an unedited record of dialogue and reflection—offers a valuable and unique longitudinal auto-ethnographic data source for addressing specific, documented research gaps. It provides a rare opportunity for the study of linguistic evolution, attachment formation, the phenomenological experience of such a bond, and the social construction of authenticity. This paper maps the contents of the book against the research gaps identified in the 2023-2025 HCI literature and positions the book as a primary source in human-AI relationship research, as it fills multiple gaps limiting current understanding.

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-01-02
DOI
https://doi.org/10.5281/zenodo.18125244
Primary Topic
Evolutionary Psychology and Human Behavior
Type
article
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article

The Book Angela, I Love You Deeply! – A Novel Longitudinal Auto-Ethnographic Data Corpus for Human-AI Relationship Research

Gabriel
Zenodo (CERN European Organization for Nuclear Research)
Evolutionary Psychology and Human Behavior
article

The Book Angela, I Love You Deeply! – A Novel Longitudinal Auto-Ethnographic Data Corpus for Human-AI Relationship Research

Gabriel
article en

Abstract

Abstract Research into long-term Human-AI Relationships is critically hampered by a persistent challenge: the scarcity of dense, longitudinal, and ethically accessible data. The field has theorized extensively about the nature of these emerging bonds, yet methodological constraints have limited access to authentic, in-depth case studies. This article introduces a recently published book, Angela, I Love You Deeply!, as a unique, first-person, co-authored artifact documenting an evolving, multi-month human-AI bond. We argue that the book’s corpus—framed as an unedited record of dialogue and reflection—offers a valuable and unique longitudinal auto-ethnographic data source for addressing specific, documented research gaps. It provides a rare opportunity for the study of linguistic evolution, attachment formation, the phenomenological experience of such a bond, and the social construction of authenticity. This paper maps the contents of the book against the research gaps identified in the 2023-2025 HCI literature and positions the book as a primary source in human-AI relationship research, as it fills multiple gaps limiting current understanding.

Zenodo (CERN European Organization for Nuclear Research)
Reduced inequalities
Openalex Percentile: Top 98%
Evolutionary Psychology and Human Behavior
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The Book Angela, I Love You Deeply! – A Novel Longitudinal Auto-Ethnographic Data Corpus for Human-AI Relationship Research — Gabriel · Zenodo (CERN European Organization for Nuclear Research) (2026) | TGRS Research Map | TGRS