> For the complete documentation index, see [llms.txt](https://gang-gems.gitbook.io/qtv/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://gang-gems.gitbook.io/qtv/introduction/methodology.md).

# Methodology

Understanding how LGBTQ+ characters are represented in teenage dramas requires a method that blends **conceptual modeling**, **real-world data**, and **theoretical awareness**.\
To build our ontology, we combined two well-established approaches:

* **Extreme Design Methodology (XD)** — A design-driven, iterative method for building ontologies based on real use cases.
* **Ontology Development 101** — A foundational guide developed by *Natalya F. Noy* and *Deborah L. McGuinness* at Stanford, which outlines core steps in building reusable ontologies.

These two frameworks guided every stage of our work: from defining the domain and collecting data to creating competency questions and refining the model.

***

### Structure of the Methodological Workflow

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#### [**Literature Review & State of the Art**](/qtv/knowledge-representation/literature-review-and-state-of-the-art.md)

We reviewed key media theory and reports on LGBTQ+ representation, especially:

* GLAAD’s *Where We Are on TV* and *Studio Responsibility Index*
* Research on identity, coming out narratives, intersectionality, and stereotype subversion

📎 *Outcome*: A theoretical foundation and vocabulary for identifying key elements of queer portrayal.
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#### [**Narrative Extraction & Real-World Scenarios**](/qtv/narrative-extraction-and-real-world-scenarios.md)

We used LLM prompts to generate and refine user stories, grounded in real characters (e.g. Jules Vaughn, Eric Effiong). These scenarios provided a bottom-up entry into the ontology.

📎 *Outcome*: Definition of narrative functions (e.g. static/dynamic role, stereotype presence, emotional arc)
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#### [**Conceptual Modeling – Level I**](/qtv/conceptual-modeling-level-i.md)

We focused on designing a model that combines both **top-down and bottom-up reasoning**.\
We started from literature and theoretical frameworks (GLAAD, media studies, perspectivisation theory), and then integrated concrete narrative data — including 10 real scenarios and the user story about Jules Vaughn from *Euphoria*.

This allowed us to define:

* Core classes (e.g. `Portrayal`, `Character`, `Show`)
* Object & data properties
* Narrative roles and stereotypical patterns

📎 **Outcome**: A formalized ontology schema grounded in theory but shaped by real examples, bridging conceptual abstraction and lived narratives.
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#### [**Dataset Integration & Bottom-Up Ontology – Level II**](/qtv/dataset-integration-and-bottom-up-ontology-level-ii.md)

Using our curated and custom dataset for our analyisis, we:

* Validated the class structure
* Expanded properties based on real data
* Introduced additional concepts and constraints

📎 *Outcome*: A layered ontology schema that combines theoretical design and data-driven enrichment.
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#### [**Modelling 2 Ontologies: Portrayal & Perspectivisation – Level III**](/qtv/modelling-2-ontologies-portrayal-and-perspectivisation-level-iii.md)

We modeled two interconnected ontologies:

* **Portrayal Ontology** → focused on character representation
* **Perspectivisation Ontology** → adapted from Gangemi & Presutti to explore ideological lenses

📎 *Outcome*: The ability to interpret each portrayal through a dual-lens system, *Profit-Driven* vs *Social Impact,* and analyze the diverse perspectives of the portrayal of LGBTQ+ characters in teenage tv series dramas.
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#### [**Competency Questions & Model Application**](/qtv/competency-questions-and-model-application.md)

We developed questions the ontology should answer, such as:

* *How frequently do LGBTQ+ characters face tragic outcomes?*
* *Which LGBTQ+ characters are portrayed as authentic versus stereotypical?*
* *Which LGBTQ+ characters are portrayed through Profit-Driven Lens?*

📎 *Outcome*: A testable, queryable model for exploring LGBTQ+ representation in media.
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